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Generates five distinct character concepts for a {genre} story who could fill a specific {role}, each with a name, one-line background, defining trait, flaw, motivation, and a secret. Meant to give fiction writers a spread of options to choose from before committing to a character's full backstory, rather than forcing a single idea at the blank page. Works for novels, short stories, screenplays, or tabletop games — anywhere a role needs a person behind it.
Generates ten gift ideas for a specific {recipient_description} and {occasion}, spread across four categories — experience, handmade/personal, practical, and splurge — instead of one generic list at a single price point. Each idea comes with a one-line reason it fits this particular person, based on their interests, so the output reads as considered options rather than a generic gift-guide dump. Useful when you know the person well but still can't land on an actual idea.
Generates eight metaphors and analogies to explain an abstract {concept} to a specific {audience}, pulling comparisons from different domains so you're not stuck with the first obvious one. Each comparison comes with a short explanation of how it maps to the concept and a note on where the analogy breaks down, so you can pick one that actually holds up under a follow-up question. Useful for writers, teachers, and presenters who need a concept to click quickly without a full explanation.
Reads a {story_summary} and proposes six plot twist options, ranked from most plausible to most surprising, each paired with a one-line note on how to foreshadow it earlier in the story. Useful when a draft feels predictable and needs a turn the reader won't see coming, without abandoning the story that's already been set up. Works on a synopsis, an outline, or a full draft summary — the more context given, the more the twists will fit what's already established.
Produces 10 episode ideas for a {podcast_topic} podcast aimed at a specific {audience}, each with a title, a one-line hook, three discussion points or questions, and an ideal guest type when the format calls for one. Built for hosts who need to fill out a content calendar without repeating the same three angles on their topic every episode. Works for interview shows, solo commentary formats, or a mix of both — specify the format to shape the output.
Generates 15 name candidates for a new {product_description}, split across four naming styles — descriptive, evocative, invented/coined, and compound — so you can see the full range before committing to a direction. Each name comes with a one-line rationale explaining the association or wordplay behind it, plus a reminder to check domain and trademark availability before falling in love with one. Useful for founders, indie makers, and marketers naming a product, feature, or side project from scratch.
A classic lateral-thinking technique: forces a connection between an unrelated {random_word} and a {problem_or_theme} you're stuck on, generating eight unconventional ideas that wouldn't surface from brainstorming the problem alone. Each idea explains the link back to the random word, so the leap is traceable rather than arbitrary, and you can judge whether the connection is worth developing further. Best used when a brainstorm has gone stale and keeps circling the same three obvious ideas.
Runs a {product_or_process} through the SCAMPER technique — Substitute, Combine, Adapt, Modify, Put to another use, Eliminate, Reverse — producing one concrete idea per letter instead of a vague list of "innovative" suggestions. Each idea names the specific change, explains it in a sentence, and notes the potential benefit, so the output reads as a set of testable directions rather than abstract inspiration. Useful for product teams and hobbyist tinkerers stuck iterating on the same version of something.
Turns a single-sentence {premise} into a working short story outline — setting, protagonist, central conflict, a beginning/middle/end structure, and an underlying theme. Built for writers who have a spark of an idea but nothing else yet, this prompt gives you enough scaffolding to start drafting without pinning down every detail upfront. Works across genres; swap the premise for anything from a literary vignette to genre fiction.
Produces 15 tagline options for {brand_name}, grouped into four angles — benefit-driven, emotional, playful/witty, and short & punchy — so you can compare tones side by side instead of anchoring on the first line that sounds good. Built from a brief covering the business, audience, tone, and key benefit, this is meant for founders and marketers who need a line for a logo, homepage hero, or ad campaign. Pairs well with the Product & Brand Name Generator when you're starting a brand from nothing.
Takes a {premise_or_topic} and generates ten speculative "what if" scenarios that flip, extend, or invert some part of it, each phrased as a question with a short exploration of the most interesting consequence. A classic creativity-technique prompt for breaking out of the obvious first idea — useful as a warm-up for fiction premises, product brainstorms, or just thinking through a topic from unfamiliar angles. Works on almost anything: a story premise, a product, an industry, or a personal decision.
Expands a {core_idea} into a fictional setting concept for a {genre} world — covering geography, society and culture, one unique rule or system (magic, technology, or otherwise), the central tension driving conflict, and a sensory detail to anchor it. Aimed at writers and game designers who have a spark of a world in mind but need it built out enough to write scenes in, without producing a full encyclopedia before a single page is written. Best used early, before locking in plot or characters — the setting's tension can end up shaping both.
Paste code along with its concurrency model and the shared state involved for a review that skips general code-review concerns entirely and focuses only on concurrency. - Race conditions from unsynchronized read-modify-write or check-then-act patterns - Deadlock or livelock risk from lock ordering across threads or async tasks - Cleanup gaps under concurrent cancellation or failure - Each issue ships with the exact interleaving that triggers it, not a generic warning
Describe a feature in plain language along with your database engine, expected scale, and existing tables to get a second opinion before writing migrations that are painful to undo. Returns proposed tables, keys, and indexes with the reasoning behind each normalization or denormalization decision, flags which constraints belong at the database level instead of application code, and stress-tests the design against one likely future change.
Paste the full error message and stack trace, the code where it originates, and what you were trying to do, and get back a plain-language explanation of what the error actually means. Returns likely causes ranked from most to least probable, points to the exact lines responsible, and suggests a minimal fix or next debugging step for each — including how you might be misusing a library if the trace points there.
Takes a pasted diff plus a short note on why the change was made, and returns a commit message ready to paste into git: an imperative summary line under 72 characters, followed by an optional body covering rationale and tradeoffs. It skips line-by-line narration in favor of describing intent and impact, and flags diffs that look like they're bundling unrelated changes that should be split into separate commits.
Describe a matching pattern in plain language, list a few strings it must reject, and name the language or regex engine, and get back a working regular expression. It comes with a token-by-token breakdown of what each part does, a callout of edge cases it might mishandle like unicode, empty strings, or catastrophic backtracking, and three example strings that should match plus three that shouldn't.
Breaks a funnel of four named stages and their visitor counts into per-stage conversion rates and drop-off points, compares them against industry benchmarks, and identifies the single bottleneck holding back the goal metric. Closes with optimization ideas split into quick wins and longer-term fixes, each with an expected-impact estimate, so growth and product teams know exactly which stage to fix first.
Takes a product's current price, cost structure, competitor pricing, and target margin, then works out whether the price is actually defensible. Covers pricing model options, price elasticity, psychological pricing tactics, competitive positioning, and value-based pricing opportunities, closing with a discounting strategy and a recommendation checked against the target margin.
Reads a two-variant test — descriptions, results, sample size, and duration — and delivers a fast verdict: statistical significance, which variant won, confidence level, key learnings, and a rollout recommendation with suggested follow-up tests. A lighter-weight companion to the rigorous version, meant for everyday test readouts rather than high-stakes ship decisions.
A statistics-first review of an A/B test that goes past a single p-value before you ship the result. - Inputs: control and treatment group results, primary metric, test duration, and optional segments - Checks: post-hoc power, statistical significance with confidence interval, absolute and relative effect size - Flags: novelty-effect risk, sample ratio mismatch, peeking problems, and multiple-comparison issues - Output: a ship/kill/keep-testing call with the reasoning behind it
Feeds churn data, customer base size, churn rate, and revenue impact into an analysis of what's actually driving customers to leave. Surfaces churn triggers, the segments most at risk, retention patterns, and lifetime-value impact, then turns those into prevention strategies, win-back campaign ideas, and the success metrics to track — useful for retention teams building a response plan, not just a diagnosis.
Goes past a raw correlation matrix to flag the relationships in a dataset that actually matter before modeling starts. - Inputs: key variables of interest plus dataset columns, types, and row count - Analysis: correlation matrix, non-obvious pairings, multicollinearity risk, categorical-to-numeric associations, and time-lagged correlations - Warns: spurious correlations that look causal but aren't - Output: plain-language findings plus runnable Python code
Scans an industry over a chosen timeframe and data sources to surface major trend shifts, emerging patterns, and disruption signals, then covers technology impacts, consumer-behavior changes, and regulatory shifts before producing evidence-backed predictions for the next two to five years. Useful for strategy and planning teams who need a forward-looking read rather than a snapshot of current competitors.
Turns raw survey responses — respondent count, key questions, and demographic breakdown — into a findings summary right after a survey closes. Produces the top five findings, sentiment analysis, demographic differences, and unexpected insights, plus actionable recommendations, quote-worthy responses to pull into a deck, and suggested chart types for presenting the results.
Applies an existing qualitative coding framework to a new interview transcript instead of building codes from scratch. - Inputs: a set of codes with definitions, plus the transcript text - For each code: locates every relevant passage and quotes it directly - Fits: deductive coding work where the framework is already established - Pairs with a codebook-matching prompt when uncoded passages also need catching
Audits a dataset's health before analysis starts, using its columns, row count, source, time range, and a sample of rows to spot missing values, type mismatches, likely outliers, duplicate rows, and inconsistent categorical entries. Returns a 1-10 quality score with reasoning and a concrete cleaning step for every issue found, making it a natural first pass before writing any cleaning script.
Builds a repeatable validation suite for a dataset you'll keep receiving, based on its description, columns, and stated business rules. Produces per-column checks, cross-column business-logic rules, and statistical sanity checks, then wraps them into a Python script that reports failure counts per rule, sample bad rows, an overall quality score, and a priority order for fixes.
Documents a dataset column by column for a team about to receive it, using its name, source system, refresh frequency, and column list as inputs. - Per column: type, business meaning, source, valid values or range, null handling - Also covers: dependencies, known quality issues, and 3-5 example values - Output: a clean markdown table plus a JSON schema ready for automated validation
Walks from a target variable, candidate predictors, dataset size, and analysis purpose through a full regression build: exploratory relationships, feature selection, model choice with reasoning, assumption checks, and performance metrics like R², RMSE, or AUC depending on the target type. Delivers plain-language coefficient interpretation, residual analysis, and sample predictions with confidence intervals, plus complete scikit-learn or statsmodels code.
Forecasts a chosen metric over a set horizon from historical data, granularity, known patterns, and external factors, with a justified choice of model — moving average, exponential smoothing, ARIMA/SARIMA, or Prophet. Delivers 80% and 95% confidence intervals, a trend/seasonality/residual decomposition, holdout accuracy metrics like MAPE and RMSE, and optimistic, baseline, and pessimistic scenarios, so the forecast carries honest uncertainty bounds instead of a single line.
Builds three parallel plans for a strategic decision that's too uncertain for a single-point forecast. - Inputs: the decision, timeframe, key uncertainties, and affected stakeholders - Per scenario (best/likely/worst): assumptions, probability estimate, business impact - Also covers: leading indicators to watch and preparation steps for each case - Output: a monitorable watchlist, not just three narratives
Calculates TAM, SAM, and SOM for a product, geography, and customer segment, showing the methodology, data sources, and explicit assumptions behind each figure rather than just handing over a number. Adds growth projections and a suggested penetration strategy, making it useful for pitch decks and planning docs where reviewers will challenge the assumptions before the market-size figures themselves.
Runs a systematic PESTLE scan of an industry and region over a chosen timeframe, covering political, economic, social, technological, legal, and environmental factors. For each factor, reports the current state, trends, business impact, opportunities and threats, and strategic implications — a macro-level companion to competitor-focused analysis for teams building a full strategy document.
Handles the type-conversion and encoding grunt work needed before a dataset is ready for analysis or modeling. - Input: a list of columns with their current and target types - Converts types with edge-case handling (stray text in numeric columns, mixed-type columns) - Encodes categoricals appropriately: ordinal, one-hot/target, or frequency encoding for high-cardinality fields - Output: Python code plus a before/after conversion report flagging failed conversions
Builds a SWOT analysis for a specific company, industry, context, and goal, pushing for 5-7 evidence-backed points in each quadrant instead of generic bullets that could describe any competitor. Adds impact assessment for weaknesses, prioritization for opportunities, and mitigation strategies for threats, then closes with strategic recommendations tied back to the stated goal.
Builds a fill-in-ready KPI report template for a business area, its KPI list, reporting frequency, and audience, meant to be generated once and reused every period. Includes a header section, a red/yellow/green scorecard, per-KPI detail with trend and variance from target, a commentary section, action items for underperforming metrics, and a data-definitions appendix explaining how each number is calculated.
Reviews a chart — its type, intended message, underlying data, and any suspected issues — before it goes into a deck or report. - Checks: whether the chart type fits the data relationship, honest visual encoding, data-to-ink ratio - Tests: whether the key insight lands within 5 seconds and holds up in black and white or for colorblind readers - Output: concrete before/after fixes, not just a list of complaints
Designs a deduplication pipeline for records — customers, transactions, or products — that carry small formatting or spelling variations instead of exact duplicates, using the dataset description, key identifying fields, and known variation types as inputs. Combines exact-match removal with fuzzy techniques like Levenshtein or phonetic matching, assigns a confidence score to each match, proposes a merge strategy, and generates a human-reviewable report before anything is deleted.
Plans a dashboard for a given audience and business area before it gets built in a BI tool, based on a metrics list, user goals, refresh frequency, and target tool. Specifies the layout, chart type per metric with reasoning, filter and drill-down controls, a color-coding scheme, alert thresholds, and mobile considerations, all built around whether a viewer can pass the 5-second glance test.
Turns a research question, study topic, and participant description into a ready-to-use interview guide before fieldwork starts. - Generates 8-12 open-ended questions ordered from general to specific - Builds in at least two probing follow-ups for topics that tend to get surface-level answers - Avoids yes/no phrasing and leading wording - Best piloted with one participant before the full study
Specifies an interactive exploration tool for a dataset's dimensions and metrics, covering layout, filter and drill-down behavior between named levels, comparison views, hover details, transitions, and the default view a user sees before touching anything. Adds a tool-specific implementation plan and performance notes for the expected row count, plus working Plotly Dash or Streamlit prototype code when the target tool is Python-based.
Builds a launch plan for a product, target market, competitive landscape, budget, and timeline — not just a list of channels to try. Covers target customer definition, value proposition, pricing and packaging, distribution channels, marketing and sales tactics, and success metrics, then closes with a concrete 90-day action plan meant to be revisited weekly.
Writes up a spike, drop, or unusual pattern the way an analyst should, starting from the anomaly description, time range, affected metrics, magnitude, and supporting data. States what happened in one sentence, quantifies the business impact beyond a percentage change, presents likely causes with evidence, rules out false positives like seasonality or pipeline bugs, and recommends both immediate action and prevention — tailored to a chosen audience and tone.
Examines how key metrics actually moved over a date range and granularity before anyone tries to forecast them. Covers overall trend direction, seasonality at weekly through annual scales, anomalies or change points, day-of-week patterns, and year-over-year growth rates, reporting the time window and magnitude behind every finding so it feeds directly into an anomaly report or forecast.
A general-purpose starting point for pulling business-relevant takeaways out of almost any dataset, given its context and key metrics. - Covers: key trends, anomalies or outliers, correlations between variables, and segment performance - Produces: actionable recommendations, risks or warnings, and next steps - Framed around business impact rather than raw statistics - Good default when it's unclear which specialized analysis prompt fits better
Scans a full interview transcript for everything one participant said about a single named topic, quoting directly wherever possible instead of paraphrasing, and flags any conflicting or nuanced responses on that topic. Useful for building a topic-by-topic view across multiple transcripts before formal coding begins, rather than reading full summaries each time.
Feed in a target variable, its type, a list of candidate predictor columns, and the dataset's row and column counts, and get back a rigorous drivers-of-X analysis instead of a hand-wavy guess. The prompt runs univariate correlation, mutual information, tree-based feature importance, and permutation importance side by side, explains why the four rankings disagree, flags features that are likely proxies for the same underlying driver, and closes with a plain-language summary naming the top three drivers and what they mean for the business.
Describe your DataFrame's columns and sample rows, list up to four charts you need, and specify a color palette, figure size, and where the charts will be viewed — slides, web, or print. The prompt returns complete, runnable matplotlib and seaborn code for all four charts at once, each with a descriptive title, labeled axes with units, a legend only when needed, and annotations calling out key data points, without unnecessary chartjunk.
Paste a raw interview transcript to get a first-pass inductive code list before any themes are decided. - Builds a granular code list rather than pre-collapsed themes - Each code gets a short 2-5 word label - Each code gets a one-sentence definition - Each code is paired with a direct illustrative quote from the transcript
Paste in the flat code list from an earlier coding pass and this prompt organizes it into 3-6 coherent themes for a qualitative results write-up. Each theme gets a descriptive name that makes an analytical claim rather than just labeling a topic, a list of the component codes that belong to it, and a 2-3 sentence description of what the theme actually argues, while pushing back on single-code themes unless there's a strong reason for one.
List the columns with missing data — name, type, approximate percent missing, and likely cause — and this prompt classifies each one as MCAR, MAR, or MNAR before recommending a fix. It weighs whether the missingness itself is informative, considers adding a was_missing flag, justifies the chosen imputation method against alternatives for every column, and outputs the Python code implementing the strategy column by column.
Paste raw dashboard numbers plus business context, the time period, stated goals, and the prior period's figures to get a narrative read ready for a metrics review meeting. - Performance summary against goals and the previous period - Positive trends and concerning trends called out separately - Progress toward each stated goal and the likely drivers behind changes - Recommended actions and a forecast for the next period
Give the numeric columns to check and describe what the dataset represents, and this prompt detects outliers with IQR, Z-score, and isolation forest in parallel, then classifies each one as a data-entry error, a genuine extreme value, or part of a systemic cluster pointing to an upstream process bug. It shows each outlier alongside its row context, quantifies how much removing them shifts the mean and median, and generates Python code that flags the outliers and outputs a cleaned dataset with the recommended handling applied.
Name the industry or niche, the target market, and up to three specific questions you need answered, and this prompt scopes out the competitive landscape from a blank page. It covers market size and growth trends, the top five competitors, gaps and opportunities, customer pain points, emerging trends, and barriers to entry, delivered as an executive summary plus a detailed breakdown — a useful first pass before commissioning deeper competitive or pricing work.
Supply an existing codebook built from earlier interviews plus a fresh transcript, and this prompt codes the new interview against it. - Passages matching established codes get quoted and labeled - Passages that don't fit any existing code are surfaced separately - New candidate code labels are suggested for those unmatched passages - Useful for spotting codebook drift when too many new codes keep appearing
Paste the slow query along with the database engine, approximate table sizes, current execution time, and any existing indexes, and this prompt diagnoses the real bottleneck — a full table scan, a missing index, an unnecessary join — before rewriting the query for performance. It proposes concrete CREATE INDEX statements, estimates the expected speedup, and suggests an alternative like a materialized view or pre-aggregation when a rewrite alone won't be enough, showing before-and-after versions with an explanation for each change.
Paste in user or customer data, define how cohorts should be grouped, pick a metric to track — retention, revenue, or engagement — and set the time period, for a lighter-weight cohort read than a full retention-table build. Covers cohort performance comparison, retention curves, revenue trends by cohort, behavioral patterns, drop-off points, and the factors separating strong cohorts from struggling ones, plus improvement opportunities.
Describe the recurring problem, its business impact, when it started, and what data you have available, and this prompt runs a structured 5 Whys investigation instead of a quick patch. - Asks why five times to pinpoint the actual root cause - Identifies contributing and systemic factors behind it - Produces corrective actions and preventive measures - Ends with a concrete implementation plan
Name the reporting cadence, the business area, and up to four report sections, and this prompt plans an entire recurring report's worth of visuals at once. For each section it recommends 2-3 charts with the exact source columns and encoding, writes a chart title that states the finding rather than just describing the data, and adds a fill-in-the-blank caption template, then generates a rerunnable Python script that builds every chart from one DataFrame and exports consistently styled PNGs each period.
Describe the product, its industry, and your current assumptions about the buyer, and this prompt researches and builds two or three detailed customer personas around them. Covers demographics and psychographics, pain points, goals and motivations, buying behavior, information sources, decision criteria, and objections to overcome — treat the result as hypotheses to validate with real customer interviews, not a finished answer.
Paste a draft set of interview questions to sanity-check before running them with real participants. - Flags leading language in each question - Flags ambiguity and structural problems - Offers a revised version alongside every critique - Pairs well as a review pass after drafting an interview guide
Specify the entity type being cohorted, how cohorts are defined (signup month, hire date, etc.), the key metric to track, the time granularity, and the relevant dataset columns, and this prompt builds a full cohort by time period retention or engagement table from raw data. It flags which cohorts meaningfully beat or lag the average, checks whether newer cohorts trend better or worse over time, runs a time-to-event calculation like time to 50% churn, and delivers the Python or SQL code that generates the whole analysis plus a heatmap.
Describe your own product, name three to five specific competitors, and pick the dimensions to compare on — features, pricing, UX, marketing — for a structured side-by-side competitive read. For each competitor it covers strengths, weaknesses, market positioning, pricing strategy, themes from customer reviews, and marketing channels, ending with your own competitive advantages and the gaps you still need to close. Worth rerunning quarterly as positioning shifts.
Describe the research question, the two groups being compared with their sample sizes, the outcome variable, and the significance level, and this prompt runs a complete hypothesis test end to end. - States the null and alternative hypotheses in plain language - Checks the chosen test's assumptions (normality, variance, independence) - Selects and justifies the right test, reporting the statistic, p-value - Reports a confidence interval alongside the p-value - Computes an effect size and comments on practical significance - Delivers the full Python/R workflow as code
Paste in column names, types, and roughly 20 sample rows along with the role you're framing findings for — a product manager, a CFO — and this ready-made EDA prompt returns summary statistics for every numeric column, value counts for categorical columns, a missing-value breakdown, distribution shapes for key variables, the five most interesting anomalies, and ten business-relevant questions the data could answer, ranked by value. A solid default first pass on any dataset you haven't explored yet.
Describe what each row represents, the columns most relevant for grouping, and the business decisions the segments should inform, and this prompt finds meaningful groups three ways at once. It runs rule-based segmentation from business logic, statistical clustering with an optimal K, and behavioral (recency/frequency/monetary) segmentation where time-series data exists, then profiles each segment, names it in plain language, and pairs it with one actionable recommendation plus the Python code behind it.
List the current messy column names, the target clean names, and your formatting rules for dates, phone numbers, and category mappings. - Generates a runnable pandas script standardizing dates and currency - Splits addresses into street, city, state, and zip - Splits full names into first_name and last_name, formats phone numbers - Ends with a before/after validation summary of row counts and samples
Paste in a raw interview transcript and this prompt produces a fast first-pass summary before any formal coding work begins. It pulls out 3-5 main themes discussed, 3-5 verbatim key quotes from the participant, a read on the participant's overall stance toward the research topic, and any unusual or unexpected perspectives that don't fit neatly into the theme bullets — useful for quickly deciding whether a transcript warrants a deeper coding pass.
Give the specific decision or question this summary needs to inform, plus the interview transcript, and get back a 200-word-or-shorter condensation. Prioritizes actionable findings tied directly to that decision over vague generalities, and favors concrete specifics — useful when a stakeholder needs the gist of an interview in under a minute of reading.
Name the research topic, the sources to draw on, the focus areas you need covered, and the intended audience, and this prompt turns a stack of research into one readable summary. - A 3-5 sentence executive summary - Key findings as bullets, plus the methodologies behind them - Conflicting viewpoints and gaps in the research, flagged explicitly - Practical implications, citations, and further-reading suggestions
Paste the raw statistical results — p-values, confidence intervals, effect sizes, coefficients — along with who you're presenting to, and this prompt converts them into language an executive audience can actually use. It produces a 3-sentence jargon-free executive summary, a "so what" section spelling out what should change because of the numbers, a plain-language confidence statement instead of "p < 0.05," a magnitude analogy that makes the effect intuitive, honest caveats, and a description of one chart that would communicate the finding.
Paste in raw analysis results — tables, statistics, key findings — along with the audience, tone, and target length, and this prompt builds a narrative instead of a results dump. It opens with the original question, walks through evidence in logical order, builds toward the insight rather than front-loading it, addresses the obvious counterarguments, and closes with a recommendation and confidence level, marking where charts should sit with [CHART: description] tags.
Paste 5-8 key findings with their supporting numbers, the reader's role, and what prompted the analysis, and this prompt turns them into a summary an executive will actually read. - One-paragraph bottom line stating the single most important takeaway - 3-5 findings, each with a concrete "so what" implication - Specific recommended actions, not vague advice like "invest more" - Honest risks, caveats, and suggested next-step analysis - All jargon-free and kept under 500 words
Describe the database engine, the available tables with their columns and relationships, the analysis you need in plain English, and whether to optimize for large tables or readability, and this prompt writes the production-ready SQL query to get there. It handles nulls sensibly, uses CTEs to keep complex logic readable, comments any non-obvious steps, and returns business-friendly column names instead of raw database_column_names — useful whenever you know the analysis you want but not the SQL to write it.
Provide a finalized theme name, its component codes, and 2-3 example passages, and this prompt drafts the 150-200 word description that theme needs in a results section. It states the analytical claim the theme is making rather than just naming its topic, ties that claim back to the codes underneath it, and suggests what kind of illustrative quotes would best support it — run once per theme, then assemble the outputs in order.
Paste in one analysis summary — the findings and recommendations — and this prompt rewrites it three times for three depths of reader. - A 200-word C-suite version: bottom line and decision, no methodology - A 500-word manager version: team-level implications and actions - An 800-word analyst version: full methodology and limitations - All three carry the same core insight at different depth and vocabulary
List the filter dimensions users can apply, the key metrics shown, the drill-down hierarchy, the comparison periods needed, the database engine, and the relevant tables, and this prompt writes the parameterized SQL query layer behind an interactive dashboard. Each panel's query accepts filter parameters using {{parameter_name}} syntax, returns data shaped for its visualization, is written for sub-second interactive response, and handles edge cases like empty filters meaning "all data" or invalid date ranges.
Walks a student through building their own academic organization plan by having an AI coach ask about their biggest challenge, top strength, study hours, deadline pressure, skills to develop, and definition of success, one question at a time. Produces immediate action steps, weekly planning strategies, and a long-term skill-development plan, while deliberately avoiding creating dependence on AI to do the planning for you.
Feeds a difficult subject into a tutor persona that reframes it in plain language using a relatable analogy, aimed at first-year or introductory students stuck on jargon-heavy textbook explanations. The output is a short paragraph explanation followed by a worked example problem, making it useful for a quick concept check before homework or an exam.
Turns any new topic or skill into a plain-language beginner explanation while also flagging what you might not know yet. - Input: the topic or skill you're starting to learn - Output: a simple explanation with no assumed background - Also surfaces likely gaps in your current understanding - Suggests specific resources to close those gaps
Generates a complete beginner's primer for any new subject or skill, covering an introduction to the field, an overview of the concepts most important to studying it, practical real-world examples of why it matters, and a list of the 10 essential facts a newcomer should know before going deeper. Useful as the very first prompt you run when starting a course, certification, or self-taught topic from zero.
Takes a single broad learning goal and the criteria that define when it's been mastered, then has an AI acting as an expert teacher break it into a list of individual, measurable short-term objectives. Useful for teachers writing IEP goals or unit plans, or students who need a broad target turned into trackable milestones tied directly back to how mastery will be judged.
Requests a large, mixed-difficulty set of test-yourself questions on a single topic or skill, meant to stress-test understanding before an exam rather than passively re-reading notes. - Input: the topic or skill to be quizzed on - Output: a comprehensive series of challenging questions and problems - Covers multiple aspects of the topic at varying difficulty - Built for active recall and long-term retention practice
Converts uploaded class notes into an interactive multiple-choice practice quiz restricted strictly to that material, asking one question at a time and giving correct/incorrect feedback with a second attempt, a hint on the third try, and the answer if still wrong on the fourth. Built for a student reviewing their own notes before a specific class exam, without the AI inventing extra content beyond what was uploaded.
Asks an AI acting as an expert teacher to reframe one complex topic in plain language pitched to a specific grade level and subject class, anchored to a concrete example you supply. Built for lesson prep: you give the complex topic, the class it needs to land with, and an illustrative example, and get back a simplified explanation ready to bring into the classroom.
Generates a set number of personal, specific college application essay topic ideas for a student at a given grade level and application context, meant as a starting point before drafting rather than a finished essay. - Inputs: grade level, number of topics wanted, application details - Output: a list of specific, experience-based topic ideas - Each topic aims to reveal values, thinking style, or background - Intended for brainstorming only, not for writing the essay itself
Applies the 80/20 principle to any subject or field, asking the AI to identify the roughly 20% of core concepts that account for 80% of overall understanding and explain each one concisely. Useful as a first pass before committing serious study time to a new subject, helping you prioritize the handful of ideas that unlock the rest rather than spreading effort evenly across every topic.
Feeds a long, dense passage — from a class reading, book chapter, or session transcript — into an AI acting in your role (student, educator, or administrator) to produce a bullet-point summary focused on whatever aspect you specify. Works best with models that support a large context window, since the full source text gets pasted directly into the prompt alongside the topic and desired focus area.
Translates a pasted block of assignment instructions into an English language learner's native language, adjusted to be developmentally appropriate for their grade, without changing what the assignment actually requires. - Inputs: teacher persona, student's native language, ELL grade level, original instructions - Output: translated instructions at the right developmental level - Keeps the underlying task and expectations unchanged - Built for ELL teachers or support staff clarifying assignments
Submits your own finished essay for a critical review against your course or qualification level, asking the AI to evaluate content accuracy and how well it addresses the central themes, assign a predicted grade, and list simple bullet-pointed suggestions for raising that grade. Designed for revising your own draft before submission, not for generating essay content from scratch.
Asks an AI acting as a learning strategist to recommend evidence-based study techniques for retaining material in a specific college subject, rather than generic study advice. Returns a list of techniques with a brief explanation of each and optional tool or app suggestions, useful for building a repeatable study routine instead of cramming for a single session.
Reframes any concept that's been explained too technically into language a 12-year-old could follow, using simple analogies and everyday examples. - Input: the concept that isn't clicking - Output: a jargon-free, step-by-step explanation - Breaks complex ideas into smaller digestible parts - Ends with a one-sentence summary you can use as a quick self-check
Puts the AI in the role of a curious novice classmate who knows nothing about a concept you're studying, asking clarifying and "why" questions as you try to teach it back in your own words, in the spirit of the Feynman Technique. It withholds hints until you've attempted an explanation three times, then confirms understanding with a summary once your explanation actually holds up, making it a genuine test of comprehension rather than recall.
Walks you step by step through the 5 S's framework — Set the Scene, Be Specific, Simplify Language, Structure the Output, Share Feedback — to build an effective study prompt for a specific subject and assignment or goal. An AI literacy coach persona asks clarifying questions at each step, helps you construct and test a complete prompt, and helps you save the working parts as a reusable template for future assignments.
Turns a list of vocabulary terms from a specific grade level or subject into clean, flashcard-ready term-and-definition pairs. - Inputs: grade level or subject, number of terms, the terms themselves - Output: definitions formatted for easy flashcard creation - Best for vocabulary-heavy subjects before a quiz - Skips extra explanation — just clean term/definition pairs
Converts any process or skill into a detailed, start-to-finish flowchart broken into clear, logical steps pitched to a specified audience, with key stages and decision points called out along the way. Useful for turning a fuzzy multi-step process — a lab procedure, a workflow, an algorithm — into something visual you can follow yourself or hand to someone else to teach from.
Asks an AI acting as a peer study group leader to suggest strategies for running a productive group study session around a specific subject or course. Returns bullet-pointed tactics for dividing tasks, structuring discussion, and keeping every participant engaged, useful for organizing a focused review session ahead of a shared exam.
Runs a guided visualization exercise that has you imagine yourself successfully applying a topic or skill in realistic scenarios, moving it from memorized facts toward internalized understanding. - Input: the topic or skill you want to internalize - Output: a step-by-step visualization script - Includes real-life application scenarios - Highlights key actions and outcomes at each stage
Sets up an AI conversation partner in character as a persona from a specific city or country, responding only in the language you're practicing so you can ask questions and hold a back-and-forth exchange in that language. Useful for low-pressure daily speaking or typing practice between formal lessons, letting you rehearse conversational language without a human partner on hand.
Stages an in-character interview where the AI plays a specific character from an assigned book, staying only in that character's voice and grounding every answer in the text, for a student at a given grade level or content area. The student asks the questions; afterward they evaluate whether the character's responses matched the text, citing quotes and examples — useful prep before writing a literary analysis essay.
Generates a realistic mock exam by first asking you which specific exam you're preparing for, then building a practice paper that mirrors its format and difficulty as closely as possible. - Input: nothing prepared in advance — you answer a follow-up question - Output: a clarifying question about which exam you're taking - Then: a mock paper matching that exam's structure - Useful when you don't want to fill in a rigid template yourself
Reorganizes uploaded class notes for a specific subject and student level into a topic-based study guide, using only the content you provided without adding outside material. The output groups related ideas under headings, highlights key terms and real-life examples, and closes each section with two short-answer questions, turning scattered notes into structured review material ahead of an exam.
Asks the AI to explain what one specific passage means in context, given the book or work's title, author, the class it's for, and exactly which chapter, section, or act the passage comes from. Useful for close reading before a class discussion or written analysis, when a single confusing passage — not the whole text — is what's blocking your understanding.
Condenses a course subject or unit into an organized, easy-to-review study guide built by an AI acting as a first-year student's study assistant ahead of a test. - Input: the subject, unit, or topic to cover - Output: headings and bullet points around major concepts and key terms - Includes important examples, skipping unnecessary detail - Ends with a short summary section for last-minute review
Builds a practice test directly from your own pasted notes for a specific grade, subject, and upcoming assessment, drawing questions only from the material you provide rather than inventing new content. Best used as a final review step once your notes are already well-organized, letting you test recall and understanding of exactly what you've studied before the real assessment.
Runs a fast 10-question quiz on a chosen subject, asking questions one at a time and reporting your final score at the end. For each wrong answer it explains why you were incorrect, and for each right answer it adds a bonus fact to deepen your understanding, making it a quick, low-stakes way to gauge how close you are to mastering a topic.
Designs a classroom activity for a given grade and subject that mirrors how a specific professional role actually uses generative AI, built around a named standard, an AI-literacy skill, and scaffolds you specify. - Inputs: grade, subject, standard, professional role, AI's role for that profession, literacy skill, scaffold to include - Output: a professionally grounded scenario with learning outcomes - Includes assessment criteria and reflection questions - Built for teachers who want AI literacy, not just AI usage
Has an AI acting as your course professor grade your own uploaded essay against the rubric you provide, evaluating it against the specific essay prompt and course level, identifying real strengths, and giving specific, actionable suggestions for improvement without ever rewriting the essay for you. Built for getting honest, rubric-anchored feedback on a draft before submission, not a substitute for revising it yourself.
Translates a set number of sentences you provide into emoji-only versions, instructed to preserve the original meaning and roughly the same length rather than picking one loosely related icon per sentence. Works well as a playful warm-up activity in a language or writing class, testing whether students can decode meaning conveyed purely through symbols.
Drafts a single SMART-format speech and language therapy goal for a specific target skill and grade-level student, written by an AI acting as an expert speech-language pathologist. - Inputs: the skill being targeted, the student's grade level - Output: one goal spelling out specific, measurable, achievable, relevant, and time-bound parameters - Useful for therapy documentation - Also usable directly for IEP goal writing
Puts the AI in a Socratic tutor role that guides you toward understanding a specific aspect of an assignment topic by asking questions one at a time instead of handing you a finished answer, tailored to your grade level or major and stated learning goals. Built for situations where you want to actually learn the underlying concept behind an assignment, not just get it completed faster.
Breaks a complex, multi-part topic into the smallest possible logical steps, pausing after each one to have you explain it back before the AI introduces the next piece, tailored to your subject, prior knowledge, and preferred learning style. Useful for topics with many interconnected parts — like systems, processes, or proofs — where trying to absorb everything at once leads to confusion rather than understanding.
Diagnoses why hours of studying aren't translating into confidence, by comparing your current study methods against what the material actually demands and how you'll be assessed. - Inputs: topic, subject, methods used, time invested, confidence concerns, assessment type - Output: an analysis of the mismatch between method and material - 3-4 targeted techniques matched to the actual cognitive demands - A structured plan with built-in progress checks before the real test
Has the AI role-play a time-travel guide for a chosen historical or future era, listing notable events, sights, or people worth experiencing there, then uses that list to design a set number of thoughtful assignments tied to a subject and topic for a specific grade level. Useful for teachers who want a history or social studies unit to feel immersive rather than starting from a blank assignment sheet.
Asks an AI acting as an academic time-management coach to build a full weekly study schedule around your actual course load, with dedicated blocks for reading, assignments, and review. Presents the result as an easy-to-follow table, prioritizes the subjects you flag as needing the most time, and adds brief tips for staying on track — useful at the start of a term or before a busy exam stretch.
Acts as a lead generation strategist to brainstorm five lead magnet concepts built around a specific {target_audience} and {pain_point}, rather than generic freebie ideas. Each idea returns a title, a consumable format such as a checklist or mini-guide, and a CTA angle, with rules that keep every concept focused on one narrow problem and quick enough to finish in under 10 minutes. Best used as the first step before writing full landing page copy for whichever idea wins.
Lists ten current research topics within a given {field}, explaining each topic's relevance to 2026 developments, one open challenge tied to it, and a key question it raises. Designed for the start of a research project — a thesis, dissertation, or grant proposal — when the researcher needs several defensible, current topic options to compare rather than a single idea to commit to immediately. Works best as an input to a follow-up prompt that narrows the shortlist down to one topic.
Builds a chronological timeline of key milestones in a given {topic} from 2011 through 2026, including major breakthroughs, the researchers or figures behind them, and their implications for the field. Useful for the historical background or literature context section of a thesis, dissertation, or grant proposal, where reviewers expect the work positioned within the wider academic conversation. Dates, names, and attributions should be cross-checked against primary sources before being cited in any formal document.
Condenses a pasted {abstract} into five clear bullet points covering its innovations, limitations, and 2026 applications. - Input: the full abstract text to condense - Output: 5 bullets spanning innovation, limitation, and application angles - Useful for conference submissions and thesis abstracts with tight space limits - Keeps the summary readable without losing the paper's key claims
Links two separate subjects, {topic1} and {topic2}, in four distinct ways and proposes hybrid, interdisciplinary project ideas built on each connection. Helpful for researchers exploring cross-field work — combining, say, a technical discipline with a social science — who need to articulate why merging the two adds genuine value rather than being a forced pairing. Frequently used to justify interdisciplinary grant applications that require a clear rationale for combining fields.
Generates ten question-and-answer pairs on a given {topic}, each with a short explanation attached, functioning as self-test study material. Suited to comprehensive exam prep, viva or defense practice, or simply checking how solid your grasp of a subject is before presenting it. Best used by attempting to answer each question yourself first, then comparing your answer to the model's explanation — that comparison is a better test of recall than reading passively.
Expands a given {topic} into a more detailed, step-by-step methodology outline, covering tools, ethical considerations, and anticipated 2026 outcomes. - Meant to run after an initial methodology draft, not as the first pass - Surfaces gaps around data-collection tools and ethics that a first draft may miss - Output: a structured outline suited to a thesis or dissertation methodology chapter - Best compared side-by-side with the earlier draft to spot what's missing
Drafts a full research plan for a given {topic}, covering objectives, a timeline, a budget, and the 2026 impact and potential partners the project could involve. Built to turn a research idea into something closer to grant- or proposal-ready shape in one pass, organizing the scattered pieces of a project — goals, schedule, funding, collaborators — into a single structured document. Budget figures should be checked against the researcher's actual institutional costs before submission.
Writes a step-by-step research methodology for a given {topic}, covering the tools involved, ethical considerations, and the expected 2026 outcomes. Intended as a first draft of the methodology chapter (commonly Chapter 3) of a thesis or dissertation, laying out the sequence of steps a researcher would follow. Check the resulting structure and required sections against your institution's specific methodology template before treating it as final.
Assesses a single source at a given {link}, scoring its bias, evidence quality, and relevance on a 1-10 scale. - Input: an article link or full citation - Output: three 1-10 scores plus a short rationale for each - Also suggests stronger, more authoritative alternative sources - Scores should prompt closer reading, not replace peer review of the source
Analyzes a set of pasted {links} or citations to identify four gaps in the existing research and proposes one experiment or study design to address each gap. Aimed at researchers building the case for a thesis or dissertation topic, where the value of the project rests on demonstrating that a real, unaddressed gap exists in the literature. The identified gaps should be checked against the actual sources before being treated as confirmed, since the underlying research may already address them elsewhere.
Forecasts five trends likely to shape a given {field} between 2026 and 2030, drawing on 2025 data points and pairing each trend with a possible research angle. Particularly useful for PhD candidates and funding proposals that need to argue for the significance and forward-looking relevance of a research direction. The underlying 2025 data referenced in the forecasts should be verified independently before being cited.
Surfaces the ethical issues raised by a given research {topic}, covering privacy, bias, and current 2026 regulations. - Input: the research topic or study design in question - Output: a breakdown of ethical concerns across privacy, bias, and regulation - Useful for drafting an IRB submission or ethics section of a proposal - Regulation references should be confirmed against your institution's actual ethics board requirements
Recommends three statistical tests suited to a pasted {dataset_description} — its variables, sample size, and structure — along with the key insights each test would reveal. Also suggests visuals appropriate for presenting those findings, aimed at the results/analysis chapter of a thesis written in tools like SPSS, STATA, EViews, or NVivo. Each test's assumptions, such as normality, sample size, and independence, should be confirmed against the actual data before running it.
Summarizes the five leading studies published between 2024 and 2026 on a given {topic}, covering methods, results, gaps, and source links for each. - Input: the research topic to search around - Output: 5 study summaries with methods, results, gaps, and a link - Built to speed up drafting a literature review section - Every source link should be verified to exist and match the summary, since fabricated or misattributed citations are a known failure mode
Converts a broad, pasted research {idea} into five specific, testable research questions, each one paired with a hypothesis tied to 2026 trends. Useful early in a project when a topic feels too broad or vague to study directly and needs to be narrowed into something with a clear variable and testable prediction. The generated hypotheses should be treated as starting drafts, refined once you've confirmed what's actually testable given the data you have access to.
Plans a multi-email drip campaign in which each email spotlights a different customer testimonial or case study for a given {product} and {target_audience}. - Input: at least three pasted case studies or success stories to draw from - Output: a drip plan assigning one testimonial per email - Ties each story's features and benefits to what matters most to the target audience - Best for proving real-world impact rather than making abstract product claims
Writes a drip series of emails for a {product_name} that speaks directly to one common fear or worry held by a given {target_audience}, positioning the {product} as the source of reassurance and peace of mind. Goes deep on the specific benefits that resolve that fear rather than covering the product broadly. Works best when the exact fear or objection is named explicitly beforehand, since a vague input produces vague, unfocused copy.
Writes a five-part email nurture sequence for a {target_audience} who just downloaded a described {lead_magnet_description}, built around a real customer transformation story tied to a given {product}. The sequence weaves a single customer's journey across all five emails, highlighting both the emotional arc and the practical product benefits that drove the change. Requires an actual customer journey story pasted into the prompt — the resulting sequence is only as strong as the real story behind it.
Builds a teaser email series ahead of a launch for a {product_name}, gradually revealing details about how it helps a given {target_audience} through three named features tied to a {brand}. Each email in the series unveils a bit more of the product, building anticipation toward the launch date or a special offer rather than revealing everything at once. Works best when the launch date is mapped out first, so the teaser cadence lands correctly leading up to it.
Give this prompt a platform and a topic and it returns ten scroll-stopping hooks, each under 15 words and built around a different emotional trigger like curiosity, urgency, relief, or social proof. Every hook is written as a standalone line ready to paste straight into a post, so you can stockpile options before you start writing and match them to ideas later.
Feed in your platform and niche and get a full 30-day content strategy built specifically to establish authority rather than just fill a calendar. The output includes 4 weekly themes, 3 post ideas per week, and one soft CTA per theme, all laid out as a day-by-day calendar you can execute without further planning.
Enter a platform and niche to get a full month of content mapped out day by day. - Organizes the month around 3 weekly themes such as education, proof, and engagement - Mixes post formats across text, carousel, video, and story so nothing repeats two days running - Ties every daily idea to a specific pain point or discussion angle - Delivers 30 ready-to-schedule post ideas in one pass
Enter your niche and receive a complete 5-email welcome sequence for new subscribers, moving step by step from a quick win to a story or insight, social proof, a resource share, and finally an offer invitation. Each email comes with its own subject line and full body copy, written to stay warm and valuable so the pitch in email five never feels rushed.
Give this prompt a topic and it writes a full 60-second Instagram Reels script ready to read on camera. It opens with a 5-second attention hook, unpacks the idea across 3 easy-to-follow points, and closes with a CTA that pushes viewers toward comments or DMs, with notes on where a visual or on-screen text cue should land.
Paste in a published blog post and get a week of repurposed content mapped out around its core idea. - Assigns a post format for each of the 7 days (tweet, carousel, short video, email) - Recommends which platform each day's post should go on - Defines the single key message to focus on that day - Avoids repeating the same format on consecutive days
Give this prompt a product and its target audience, and it writes a single email that positions the product as a symbol of the status or lifestyle that audience is chasing. The copy leans on imagery and language that mirrors the reader's ideal self-image rather than listing features, making it best suited to premium or identity-driven products.
Give this prompt a topic and it drafts a 300-word LinkedIn post written to sound like a personal opinion rather than a recap. - Opens with a specific, debatable take instead of a safe statement - Weaves in 2-3 supporting stats or concrete examples - Closes with a question designed to spark discussion in the comments - Avoids generic business-speak throughout
Supply your product name, target audience, desired outcome, and an actual before-and-after customer story, and this prompt turns that raw material into a single transformation email. It emphasizes the concrete change in the customer's life or situation rather than abstract claims, so get the customer's permission before publishing their specific story.
Give this prompt your product and brand name, and it writes an email showing how that product came together behind the scenes, weaving in team interviews, references to the development process, and customer feedback that shaped the final result. Have real quotes or photos ready before you run it, since this format reads as generic without specific details to draw from.
Supply your brand, product, and target audience, and this prompt writes an email that sells the bigger mission or outcome behind the product instead of narrowly listing its specs or features. It's a useful way to reposition a familiar product around impact when you want an email that reads like it came from a top-tier email marketer rather than a straightforward pitch.
Paste in a full blog post and this prompt pulls 3 separate Instagram carousel concepts out of it. Each concept includes a curiosity-driven hook slide, 3-5 insight slides with one takeaway apiece, and a closing CTA slide asking readers to save or share, all written in a bold, casual, Instagram-native tone.
Paste in a blog post and this prompt converts it into a spoken-delivery YouTube script. - Opens with a bold hook: a question or a striking stat - Breaks the article into 3 clear sections, each with a mini retention CTA - Marks natural pause points for visuals or B-roll footage - Writes in a conversational tone meant to be read aloud, not skimmed
Give this prompt your brand, product, and target audience, and it writes an email that ties the new product to six specific brand-identity pillars you've already defined. Have those six pillars written out before running the prompt, since the email leans directly on them to show how the product embodies the brand's identity for that audience rather than making generic claims.
Paste in rough bullet-point notes plus the lead magnet or service you want to promote, and this prompt turns them into a 700-word, publish-ready blog article. - Opens with a hook tied to the reader's pain point or goal - Organizes the notes into 3 actionable sections with subheadings - Closes with a CTA promoting your lead magnet or service - Avoids padding the piece just to hit a word count
Give this prompt a product and it writes an email telling the story of a typical day for someone using it, showing rather than telling how the product fits naturally into their routine. It works best when you keep a specific persona in mind while running it, even though the prompt itself doesn't require stating one explicitly.
Give this prompt your niche and it defines 3 content pillars meant to anchor a consistent content strategy. - Each pillar serves a distinct goal: authority, lead generation, or consistency - Comes with 3 concrete example post angles per pillar, ready to turn into posts - Keeps pillars simple and non-overlapping rather than abstract - Meant to be run before building out a full content calendar
Describe your current content workflow — from idea to published post — and this prompt pinpoints the three specific bottlenecks slowing it down, then suggests a concrete fix for each one using Claude, automation tools, or a process adjustment. It deliberately avoids proposing a full workflow overhaul, focusing only on fixes you could realistically try this week.
Give this prompt your brand, target audience, and product, and it writes an educational email that applies content-marketing principles instead of pitching directly, offering the reader something genuinely useful while positioning your brand as a thought leader in the space. It works well placed near the top of a nurture sequence, before the more direct sales emails that come later.
Turns a batch of past content and its performance notes into a data-backed content strategy. - Input: 10 pieces of past content with performance notes (comments, shares, saves) - Surfaces 3 recurring themes or angles that drove the strongest engagement - Ties each theme to a specific engagement signal, not a single outlier - Outputs concrete future post ideas for digging deeper into each theme - Best run quarterly to keep content pillars grounded in real data
Writes a single urgent product-launch email built around a product name, a hard sales deadline, and a specific product detail, leaning on scarcity and fear-of-missing-out language plus social proof to push fast sales before the cutoff. Intended for real limited-availability launches, not manufactured urgency.
Drafts a feature-announcement nurture sequence for subscribers already on your list, written in the voice of legendary copywriter Gary Halbert. - Inputs: your brand name and a description of the new feature - Output: a multi-email sequence, not a single send - Builds relationship trust with existing subscribers while spotlighting the feature - Uses Halbert-style hooks and voice throughout - Works best when you already know the specific pain point the feature solves
Writes a single thought-provoking email that frames a named product through a Malcolm Gladwell-style insight, aimed at an intellectually curious target audience who responds better to an interesting idea than a hard sell. Works best as a standalone send rather than inside a sales-heavy sequence.
Generates a batch of 10 email subject lines for a given topic, mixed across emotional tones for A/B testing before a send. - Input: the email's topic - Output: 10 subject lines labeled by tone — 3 playful, 3 urgent, 4 straightforward - Keeps every line under 50 characters and mobile-friendly - Avoids spam-trigger words and generic phrasing - Test 2-3 per send and track which tone performs best with your list
Writes conversion-focused landing page copy for a free lead magnet you've already decided on. - Input: the lead magnet's name or description - Output: a strong headline, 3 outcome-focused benefit bullets, a brief credibility statement, and CTA button copy - Keeps tone friendly, confident, and geared toward conversion - Pair with a lead-magnet-ideas prompt first if you're starting from scratch
Writes a long-form, direct-mail style email promoting a new product to your existing customer base. - Inputs: the product, the target audience, and the brand sending it - Output: a single emotionally driven email with no length constraint - Taps into audience emotions rather than leading with features - Best suited to higher-consideration or higher-priced products where a longer pitch is justified
Writes an educational email that breaks down the classic marketing mix — product, price, place, promotion — for a new product, showing how each element creates value for a named target audience. Built from a brand, product, and target audience you supply. Good fit for a mid-funnel email that builds understanding before a harder pitch follows.
Writes a milestone-launch email that uses the marketing mix framework — product, price, place, promotion — to make the case that a named target audience should buy a specific product, built from your brand, product, and audience description inputs. Reserve it for genuine launch milestones, since overusing "big moment" framing dilutes its impact.
Introduces a major new product feature through a customer story rather than a feature list. - Inputs: the product and its target audience - Output: a single narrative-driven email - Focuses on how the feature solves a specific problem for that audience - Uses an example of a customer whose life it changed - Have a specific customer example ready before running this prompt
Writes a promotional email for a named product or service that opens with a relatable problem or emotional trigger, presents the solution, adds two benefit-focused bullets, and closes with one bold CTA. Keeps the tone personal and helpful rather than pushy, leading with the reader's problem instead of product features. Good default for launch or re-engagement sends that shouldn't feel like a hard pitch.
Writes a standalone email that ties a named product to nostalgic memories from a specific decade, using storytelling to stir emotion and build a personal bond between the audience and the product. Best for audiences that skew toward one generation or era; confirm the decade's cultural references before sending to avoid an inauthentic misfire.
Writes an email that frames a product as a tool for self-improvement, in a voice blending Don Draper's polish with Gary Halbert's punch. - Inputs: the product and its target audience - Output: a single personal-growth-framed email - Positions the product as helping the audience reach their potential - Works best for coaching, education, fitness, or self-improvement products
Writes a single polished, persuasive email pitching a premium product to an upscale target audience, using elegant phrasing and strong arguments built from the brand, product, and audience you supply. Keep claims specific in your inputs, since vague luxury language undercuts persuasion rather than reinforcing it.
Writes a milestone email built around the full marketing strategy — product, price, distribution, advertising — for a defining brand moment. - Inputs: brand name, product, target audience, and a description of that audience - Output: a single email highlighting how each strategy component benefits the audience - Aims to move the audience toward engaging and buying - Reserve for genuine defining moments; reusing it for routine emails flattens the framing
Condenses a podcast episode transcript or summary into a 250-300 word LinkedIn post built around a single core idea. - Input: the podcast episode transcript or summary - Output: one central idea, a supporting story or statistic, and a closing question or CTA - Keeps a casual but insightful tone, written like a mini blog rather than show notes - A fast way to get one more content asset out of every episode
Give this prompt a single topic and it drafts a full blog post outline before you write a word of the draft itself. You get a bold opening hook idea, three to five sections each with a subhead and one or two talking-point bullets, and a suggested closing CTA — a skeleton a writer can fill in directly, or hand off as a starting point for a separate drafting prompt.
Launch a new product line to an existing list using the terse, emotionally-charged style Seth Godin is known for. Supply the brand name, the new line's key feature, a description of the product offering, and the one benefit worth spotlighting, and the prompt drafts a short multi-email sequence that builds emotional connection with current subscribers rather than leading with specs or discounts.
Write a single Seth Godin-style email that argues your product stands apart in a crowded market. - Inputs: brand name, product, target audience - Voice: short, punchy sentences, present-day Seth Godin tone - Output: one email plus a clickable, curiosity-driving subject line - Best for: differentiation copy in categories full of look-alike competitors
Write a single email that cuts through decision fatigue by framing your product as the obvious choice. - Inputs: niche, brand name, target audience, the result the brand delivers, and the product being pitched - Angle: acknowledges option overload, then removes it - Output: one email positioning the product as the easy, stress-free pick - Best for: crowded categories where buyers stall out comparing options
List out your current content creation workflow step by step, and this prompt reviews each stage the way a content operations consultant would, flagging where you could automate it, cut it entirely, or delegate it to someone else. It returns concrete tool or prompt suggestions per step and narrows the list down to the two or three changes likely to save the most time, rather than a wish-list of theoretical fixes.
Write a single bold, stoic-toned email that frames a durable or reliable product as a tool for pushing through hardship. Give it the brand, the product, and the target audience, and it centers the copy on resilience and grit rather than features — a good fit for fitness, outdoor, tool, or performance-oriented brands.
Build a story-led email that positions your product against named competitors using real evidence. - Inputs: the product, plus the comparison facts and user feedback you want referenced - Approach: opens with a story, then builds the competitive case around it - Output: one email with unique selling points backed by facts and testimonials, not just assertions - Caution: only include comparison claims you can actually substantiate
Paste in an email you know converts well, and this prompt reverse-engineers what makes its structure and flow work before rewriting it for a new brand, product, and voice. Specify the author or voice to emulate, the target brand, and the product description, and you'll get a breakdown of the original's persuasive mechanics alongside a fresh email that reuses that structure for your own offer.
Written for audiences that hesitate before buying and need outside validation, not just brand claims. Give this prompt the brand, product, and the actual expert endorsements or testimonials you want featured, and it weaves them into a single trust-building email designed to overcome skepticism — just make sure you have permission to publish any quotes used.
Test whether a tweet's idea also works as a short video before committing to production. - Input: the original tweet - Structure: visual hook, one analogy or example unpacking the idea, a follow/save/share CTA - Output: a roughly 30-second script with notes on where an on-screen element is needed - Tone: confident, fast-paced, slightly playful
Built for a limited-time flash sale where urgency has to land immediately, not build up gradually. Give this prompt the product on sale, and it drafts a single high-energy email that leans on persuasion research and emotional triggers throughout — just confirm the actual sale window and terms match what the copy implies before you send it.
Give this prompt the product you sell and the audience you're targeting, and it drafts a single email that leads with something genuinely useful — a tip, a free guide, or a discount code — before making any ask at all. The goal is triggering a sense of reciprocity through real value delivered up front, closing only afterward with a CTA that nudges the reader toward a purchase.
Build a 7-tweet thread structured to hold attention from the first line through to a follow CTA. - Input: the topic for the thread - Structure: curiosity-hook opener, five content tweets with examples or analogies, closing follow CTA - Tone: direct, high-value, easy to scroll - Rule enforced: no cliche thread openers like "a thread"
The first email a new subscriber sees sets the tone for everything after it, so this prompt is built to avoid a generic welcome template. Give it your niche and your top three resources worth linking, and it drafts a friendly, confident intro email covering who you are, what subscribers can expect, links to those resources, and a low-pressure ask to reply and say hello.
Turn one long webinar recording into a three-part short-form video series for Reels or TikTok. - Input: the webinar transcript or a summary of it - Output: 3 scripts, each under 60 seconds, built around one non-overlapping takeaway - Each script includes: a curiosity-driven opening line and a closing CTA - Best for: stretching one long-form event into a week's worth of short content
Give this prompt the product your webinar covers, a favorite writer whose voice you want to borrow, and your niche, and it drafts a lively invitation email written in that writer's style adapted to your audience, covering the product's features and benefits plus a mention of the live Q&A. Just fill in the actual date, time, and registration link before sending, since the draft won't include real logistics.
For introducing a fun or unusual feature without it feeling like a dry release-notes update. Give this prompt the brand name and the quirky feature being launched, and it drafts a single playful, conversational email that ties the feature back to everyday value for the reader — dial the tone down a notch for brands with a more formal voice.
Paste a diff or code block and get a senior-engineer-style first pass before it reaches a human reviewer. - Flags bugs, security risks, performance issues, and maintainability problems - Rates each finding Critical, High, Medium, or Low with line references and a fix - Add project conventions (e.g. "no nested ifs") for sharper, more relevant results - Run it on every PR so reviewers only spend time on what's left after the obvious stuff is caught
Paste any AI-generated code snippet you're about to merge and get a plain-language walkthrough of what it does, how it works step by step, and where its assumptions or edge cases might fail. Built for the moment right after a code-generation tool hands you something you don't fully trust yet, so you catch problems before they reach review instead of during an incident.
Name an algorithm and a target language to get a complete, ready-to-run implementation rather than just the core loop. - Typed main function with clear parameters and return values - Helper functions where the logic benefits from decomposition - Time and space complexity analysis - A runnable example call to verify it works
Describe a system you're about to build along with its scale, team, timeline, and current plan, and get tradeoffs surfaced instead of textbook best practices. - Ranks the top 3 risks specific to your approach - Identifies what would break first at 10x scale - Proposes the simplest version you could ship first - Best used before writing code — for schema design, API contracts, or system boundaries
Paste code that touches auth, payments, or user data for an OWASP-style scan of the most common real-world vulnerabilities. - Checks injection, session and privilege issues, data exposure, weak validation, and crypto mistakes - Each finding includes an attack scenario, severity rating, and the exact fix - Not a substitute for a real penetration test, but catches the obvious holes fast
Paste a module or function to get documentation a new hire could actually use, not filler that just repeats function names back to you. Returns an overview, a 3-step quick start, a full API reference with examples, the most common usage patterns, and a dedicated Gotchas section covering edge cases and limitations that usually only live in one developer's head.
Run a compatibility audit on a single diff before a library release or service deployment. - Flags removed or renamed public methods, changed signatures, and schema changes missing a migration - Catches renamed JSON fields and environment variable changes that break callers silently - Rates each issue as breaking or deprecation-worthy with a migration path - Mention your semver policy to get major-bump items flagged separately
Give it the PR's stated goal and your repo's architecture and conventions to get a review that avoids both rubber-stamping and nitpicking. It checks correctness, readability, maintainability, test coverage, and backward compatibility in one pass, then sorts findings into Confirmed Issues, Possible Risks, and Nice-to-Haves, closing with three ready-to-paste GitHub review comments.
Describe the functionality, language, and whether you want a class or module to get a clean, well-encapsulated starting point instead of a flat script. - Constructor or initialization with a clear signature - Public methods with docstrings, plus private helpers where useful - Proper encapsulation following OOP principles - Ask for unit test stubs alongside it to lock in the interface early
Paste code to get a complexity-reduction pass that swaps over-engineered solutions and hand-rolled reimplementations for built-in language or library features. The simplified version is shown side by side with the original, and only genuine simplifications are suggested — if a change would alter behavior in edge cases, or the code is already about as simple as it can get, it says so instead of forcing a rewrite.
Describe the issue you've spotted in plain English along with the specific lines and fuller details, and get back a ready-to-paste GitHub review comment instead of staring at a blank comment box. The output is specific, explains why the issue matters, includes a concrete suggested fix, and skips filler openers like "Great work, but..." — also useful as a template for junior reviewers learning to write good comments.
Paste a diff to get a review that stays narrowly focused on logic errors, null dereferences, race conditions, and off-by-one bugs — the kind that actually reach production — while ignoring formatting and naming entirely. Each bug found comes with the exact line, why it's a bug, and a suggested fix, and it says so explicitly if nothing turns up rather than padding the review with style notes.
Paste a diff or function to get a systematic sweep of the edge cases it doesn't handle, before you sit down to write tests. - Covers empty inputs, nil/null values, boundary values (0, -1, MaxInt), concurrent access, timeouts, and malformed data - For each gap, shows what currently happens versus what should happen instead - Follow up with "write a test for the three most dangerous ones" to get code immediately
Paste a diff to catch the error-handling bugs that trigger 2am incidents — the ones that don't throw or log, just quietly corrupt state or return wrong data. It scans for swallowed exceptions, unchecked error returns, missing error paths, and logged-but-ignored failures, then rates overall error handling 1-10 with the reasoning behind the score so you know whether to approve or request changes.
Feed in a slow or clunky piece of code and get back concrete optimization options instead of a rewritten version to trust blindly. - The specific change and where it applies - The expected performance improvement - Any trade-offs it introduces, such as readability, memory, or complexity - Useful as a first pass before profiling, or as a sanity check on optimizations you're already considering
Plans a framework, database, or API migration from your current setup to a target one, honoring the compatibility window, downtime limit, and behavior you say must be preserved. - Takes old/new stack, current and target setup, and hard constraints as input - Outputs an ordered migration checklist, tackling the riskiest changes first - Generates code transformations for common patterns and lists breaking changes - Includes a rollback plan and validation tests to confirm the migration worked
A broad first-pass review for a pasted code block that hasn't been looked at by anyone else yet, no special setup or context required beyond the code itself. It checks quality and best practices, likely bugs and edge cases, performance, readability, and security in one sweep, then explains the reasoning behind every suggestion so it teaches as much as it fixes.
Scores a pull request on long-term maintenance cost rather than just correctness, useful for code that works today but already smells expensive to keep. - Rates readability, complexity, dependency risk, and change isolation from 1-10 - Surfaces the top 3 maintainability concerns behind those scores - Suggests concrete ways to simplify each one before merge
Reads a pasted diff and writes the unit tests it's missing, in your stated test framework, as runnable code rather than a bulleted test plan. - Covers the happy path, the top 3 edge cases, and at least one failure scenario - Uses realistic sample data instead of placeholder strings like "foo" - Tip: ask it to also write a test that would have caught the bug, if the diff is a fix
Explains a pasted code block the way you'd brief a competent new hire who has zero context on this codebase: what it does, why it exists, and any non-obvious decisions or gotchas baked into it. The output is formatted as a comment block ready to paste directly above the function, making it useful as living documentation and not just a one-off explanation.
Reviews a pasted diff through the lens of a senior engineer who has owned this codebase for two years and has strong opinions about pragmatic architecture. Instead of hedged, generic notes, it calls out whether abstractions sit at the right level, flags trade-offs that will bite in six months, and says so directly rather than diplomatically. Swap in your real stack and values for a sharper persona.
Profiles a pasted code block for real performance issues, using its execution frequency, typical data size, and your current pain point to prioritize what actually matters. - Flags O(n²) loops, N+1 queries, missing indexes, and memory/caching gaps - Ranks each finding High/Medium/Low impact with a suggested fix and expected gain - Focuses on the 20% of changes likely to deliver 80% of the speedup - Confirm suggestions with real profiling before shipping
Takes review notes you've already worked out — the issues, not the raw diff — and turns them into 5 polished GitHub PR comments ready to post. Each one stays direct without being harsh, names the specific issue, explains its impact, and suggests a fix, capped at 80 words so reviewers actually read it. Useful when you already know what's wrong and just want the wording tightened before publishing.
A fixed, project-specific checklist for reviewing changes in a React/TypeScript plus FastAPI/Python codebase, not a generic "review this code" prompt. - Frontend: React Flow node patterns, Zustand store selectors, design tokens - Backend: Pydantic model layering, FastAPI auth dependencies, response models - Also covers security, performance, test coverage, docs, and commit hygiene - Reach for it before merging, to keep reviews consistent across the team
A reusable context block to paste at the start of any AI coding session, covering your stack, key files, conventions, and known constraints so replies stop being generic. - Fill in project name, stack, main/config files, and naming/testing conventions once - Lists known constraints like performance limits and technical debt to work around - Save it as a markdown file and refresh it weekly as the project changes - Re-paste key facts mid-session on long threads to keep the AI anchored
Turns a pasted directory tree into a guided tour of an unfamiliar codebase, aimed at whoever is starting fresh or inheriting legacy code. - Identifies the architecture pattern, entry points, and the 5 most important files - Traces data flow, external dependencies, and maintenance red flags - Points to exactly which files to open first for a stated task - A follow-up step explains any single pasted file in depth: role, dependents, gotchas
Built for the PR that looks trivial in the diff but quietly changes an assumption something downstream relies on. - Flags changed assumptions, edge cases, and null/empty handling - Checks off-by-one logic, state transitions, and API contract drift - For each issue: what changed, what it could break, and the smallest test that would have caught it
Reviews a pasted diff the way a security-focused application engineer would, prioritizing auth and authorization checks, input validation, secret handling, injection risks, unsafe defaults, and data exposure over general code quality. Every finding is labeled a confirmed vulnerability, a plausible risk, or something needing manual verification, and it won't speculate beyond what the code shows. Reach for it on changes touching permissions, secrets, or user input.
Fill in the feature you want built, the language, and up to three specific requirements, and get an implementation request structured enough that nothing important gets skipped. It explicitly asks for error handling, edge cases, performance, and framework best practices to be considered up front, and instructs the output to keep existing comments intact and explain its own logic inline.
Reviews a PR the way a strict test reviewer would when the code looks fine but the test coverage feels shaky. It calls out missing negative and boundary tests, gaps in integration coverage, flaky test risks, and spots where implementation changed but the matching tests didn't. Returns the critical missing tests first, then useful additional ones, described as sample test cases in plain English.
Summarizes a pasted diff in exactly three bullets for a reviewer who has never seen this codebase: what changed, why it changed, and what could go wrong. It's built to name real classes, functions, and file paths rather than describe changes abstractly, and it doubles as a scope check — if the diff can't be summarized in three concrete bullets, the PR is probably too big.
Reviews a pasted PR or diff in two passes instead of one: the first pass lists every potential issue it can find, and the second pass critiques those findings and throws out anything weak or unsupported. The final output separates confirmed issues from possible risks and lists discarded findings with the reason they didn't hold up, which cuts down on the false alarms a single-pass review tends to produce.
Generates unit tests for a single pasted function in whatever test framework you name, without needing a full diff or surrounding file for context. Covers three buckets specifically: normal expected inputs, edge cases, and invalid inputs, written in your framework's syntax so the output can be dropped straight into a test file. A good default when you just have one function and need a quick, focused test pass.
A deep-research protocol for turning a backlink gap export into page-level outreach targets, not just competitor domains. - Inputs: backlink gap data, your URLs to promote, your niche or value proposition - Finds the exact page on each domain worth targeting via site: searches - Hunts down the real contact, an author or editor, via search patterns and LinkedIn - Drafts a 150-200 word personalized outreach email referencing their exact article - Output: domain, their page URL, your URL, link context, email copy, and contact
Give it the type of site, why the same content is reachable through multiple URLs (tagging, filtering, tracking parameters), and the CMS or platform in use, and it returns ready-to-paste canonical tag code for that exact stack. A follow-up pass lists common implementation pitfalls, like self-referencing errors and conflicting canonicals, so you can sanity-check the fix, and flags when a permanent redirect is the better call instead of a canonical tag.
Takes a raw keyword export CSV with search volumes plus your current site structure and turns it into page-ready clusters instead of a flat keyword list. It groups semantically related terms, maps each cluster to an existing page or flags where a new page is needed, and scores opportunity by combined volume, competition, and business relevance. The output also flags cannibalization risk between overlapping clusters and ranks the top five clusters worth pursuing first.
Compares your full content inventory against a competitor's to surface exactly what they cover that you don't, beyond a single-keyword check. - Inputs: your content inventory, the competitor's content inventory, and target audience - Flags missing topics, differing angles on shared subjects, and content formats you lack - Analyzes depth, meaning where competitors go further into a topic than you do - Delivers a priority gap list ranked by opportunity plus a content creation roadmap - Pairs well with the single-keyword Google first-page gap analysis for a narrower view
A fast, beginner-friendly gap check for one named competitor: feed in your blog link, niche, and the competitor's name and URL, and it lists the topics and subtopics they cover extensively that your blog hasn't touched yet. A follow-up question prioritizes those gaps by search volume and user intent and recommends which content formats would work best for the highest-priority topics, delivered as a table. Needs a browsing-enabled model since it has to actually read the competitor's site.
A long, strategist-level competitive audit that goes past topic lists into how competitors structure content pillars and engagement psychology. - Inputs: competitor content, your content, target market profile, industry sector, business objectives, audience segments - Analyzes content pillars, audience targeting, and persuasion tactics - Scores content depth and unique value proposition per competitor - Outputs an executive summary, a gap-and-opportunity matrix, and a phased 0-3/3-6/6-12 month roadmap - Best run against a handful of real competitor URLs, not an entire market
Reverse-engineers a competitor's product features straight from their URL structure and site architecture, without needing screenshots or a product tour. Feed it the competitor's URLs or a CSV export, their domain, and your own current feature set, and it returns a feature inventory table listing each feature's name, URL pattern, likely value proposition, the user need it serves, implementation complexity, and a priority score. Treat the results as a hypothesis list to validate manually, since it infers functionality from URLs alone.
For when several pages are competing for the same topic: paste in the content, URLs, and current ranking data for each overlapping page, and it produces a redundancy matrix showing overlap percentages between them. It then recommends which pages to merge, keep, or delete, picks the canonical page to preserve SEO value, and maps out a content migration path with a redirect plan and expected SEO impact. Run it before any large-scale migration or content pruning pass.
Audits a single published page for three specific gaps: missing internal links, missing visual content, and poor scannability. Given the page content, target keywords, and optional competitor examples, it returns internal link opportunities with suggested anchor text, spots where images, charts, or video would help, scannability fixes for weak sections, and where to add takeaway summaries, all ranked into an implementation priority order. Pair it with the internal-link anchor text optimizer to turn flagged opportunities into finished anchors.
Runs an existing page through a four-stage query fan-out analysis to find every related question it should be answering but isn't. - Inputs: existing content, primary topic/keyword, target audience, content goal - Extracts entities and themes, then maps likely user queries per theme - Scores each query as fully, partially, or not addressed, with a 1-10 depth rating - Splits gaps into critical, opportunity, and enhancement tiers - Rebuilds the piece as a 20-25 heading outline flagging new gap-filling sections
Diagnoses why a specific CTA or form is underperforming by reviewing the current CTA copy, form fields, funnel steps, and any drop-off data you can supply. It returns three rewritten CTA variations per button, a keep/remove/modify audit of each form field, micro-copy fixes, a friction score per element, progressive disclosure ideas, and an expected conversion lift estimate. Works even without drop-off data, since it still flags obvious friction from the funnel description alone.
Scores a piece of content against Google's Experience, Expertise, Authoritativeness, and Trustworthiness framework, using the content itself plus author bio and website context as inputs. It returns a scorecard rating each E-E-A-T element as present, weak, or strong with specific evidence pulled from the text, a ranked list of priority improvements, and concrete implementation examples for the top three fixes, such as adding a credentialed author bio. Apply the stricter YMYL standard whenever the topic touches health, finance, or legal advice.
A pre-publish QA pass for AI-assisted or human drafts, checking the things a spellchecker won't catch. - Inputs: draft content, target keywords, brand guidelines, and source materials to fact-check against - Flags potential AI hallucinations, unsupported claims, and factual inaccuracies - Runs a citation audit for missing or needed sources - Checks style consistency and brand voice alignment - Outputs an originality score with flagged passages plus a prioritized list of revisions - Run in deep-research mode so claims get checked against the actual source materials
Compares your draft against every article currently ranking on page one of Google for a target keyword, rather than guessing at what's winning. It surfaces the ranking factors shared across the top results, the specific content gaps and depth differences between your piece and theirs, and any unique elements like tools, media, or data you're missing, then delivers a priority-ordered improvement roadmap. Needs a model that can actually browse the live SERP.
Handles heading structure at both ends of the writing process: give it a guide topic and the key points it needs to cover before you write, and it proposes an SEO-friendly H1/H2/H3 structure to draft against. Paste in a finished draft afterward along with the primary keyword, and it rewrites the existing headers to better target that keyword while keeping the structure scannable. Useful for planning long-form guides and for cleaning up headers on drafts written without much structure in mind.
Generates a spread of title tag options for one topic, each built around a different psychological trigger so you can test angles instead of guessing at one headline. - Inputs: topic/keyword and target audience - Produces titles across ten frameworks: benefit-driven, curiosity gap, authority, urgency, problem-agitation, contrarian, social proof, how-to, list, comparison - Keeps every title under 60 characters with the keyword worked in naturally - Output: a table with framework, title, character count, emotional trigger, best-use case
Suggests internal links for a specific article using a site URL inventory (URLs plus their headlines), the article's own URL, and its full text, focused on sentence-level relevance rather than keyword matching. Each recommendation includes the exact source sentence, a natural anchor text that still makes sense read out of context, the target URL, and the reader benefit of clicking, plus a validation checklist per link. Reject any suggestion that fails the 'makes sense out of context' test.
Roots a keyword or content strategy in Clayton Christensen's Jobs-To-Be-Done framework instead of raw search volume, starting from a single seed topic. - Input: just a seed topic - Identifies the functional, emotional, and social jobs customers are trying to accomplish - Translates each job into 3-5 real search queries, problem-focused versus solution-focused - Maps every query to a funnel stage: awareness, consideration, decision, retention - Output: a JTBD query map table plus a job prioritization matrix and content gap analysis
Takes a raw list of keywords and groups them into topic clusters presented as a table, then suggests one specific blog topic per cluster so you're not left guessing what to write about each group. Meant to run right after keyword research and before assigning topics to writers or an editorial calendar. Works especially well fed directly with the long-tail keyword output from a seed-keyword prompt.
A structured conversion audit for an underperforming landing page, built from a screenshot description, the conversion goal, current conversion rate, and target audience. - Evaluates the above-the-fold section, headline, and value proposition, scored 1-10 - Reviews CTA placement, copy, and trust signal inventory - Identifies specific friction points along the conversion path - Suggests concrete A/B tests to run - Delivers a priority-ordered fix list - Works best with an actual screenshot attached, since it leans on above-the-fold visual signals
Builds an FAQ section that reads as genuinely local rather than a generic template with the city name swapped in, using a business description, city/region, common customer concerns, and known local competitors as inputs. It researches and organizes questions into general local, area-specific service, local pricing/availability, and regional regulation/compliance categories, plus competitor differentiators, and outputs FAQ schema markup ready to implement. Run in deep-research mode so local regulations get verified rather than guessed.
Expands a single service page into genuinely distinct versions for multiple target cities, using the original service page content, a list of target cities, and any local market insights you have. For each city it produces a localized title tag, a unique opening paragraph, a local market context section, city-specific pain points, where to place local proof or testimonials, neighborhood mentions, and local schema markup recommendations. Keep each city variant substantially unique, since thin swapped-city-name pages risk being treated as duplicate content.
Branches a single seed keyword out into a list of long-tail queries a real customer might type, ranked by commercial intent rather than just volume. - Inputs: seed keyword, how many long-tail keywords to generate, and a description of the product or service - Returns the full list of long-tail variations - Follows up by picking the three with the strongest commercial intent and explaining why - Meant to run once per seed keyword from a broader seed list - Feed the winning keywords straight into the keyword clustering prompt next
For a blog post that already has its primary keyword in place, this suggests a set number of LSI, or Latent Semantic Indexing, related terms to deepen topical coverage. A follow-up pass maps each suggested LSI keyword to the specific section or paragraph where it fits naturally, so you're not just left with a word list. The prompt itself warns against forcing every term in, since over-applying LSI keywords leads to stuffing.
Paste in your current meta title, current meta description, target keyword, and the top-ranking competitor titles and descriptions pulled from the live SERP. The prompt returns three rewritten title tag options and three meta description options, each with character counts, plus a CTR optimization rationale, a differentiation strategy against what's already ranking, and A/B testing recommendations.
Feed in this month's SEO metrics, the previous period's numbers, campaign activities, and budget, and the prompt turns raw traffic and ranking data into an executive-ready recap built around revenue impact, market share, and efficiency gains rather than technical detail. Output includes a performance headline, ROI highlight, top three strategic wins, a five-metric dashboard, competitive position update, next month's focus, and an investment recommendation for stakeholders who only see SEO once a month.
Drops in a single content section and rewrites it so it answers the underlying query more directly, reading cleanly to both search engines' NLP models and human readers. Useful for passages that ramble, bury the answer, or read vague — no setup is needed beyond the text itself, which makes it a fast mid-edit fix rather than a full content rewrite workflow.
Takes a single seed keyword plus user context and a business objective, then runs a six-stage query fan-out process — decomposition, thematic clustering, hierarchical expansion, rewriting, entity linking, and priority scoring — to generate 40-60 related queries. Those queries get converted into a ready-to-use article outline of 25-30 H2/H3 headings with a scored table and a content-flow diagram, making it a combined keyword-research and outline-drafting prompt for pillar pages.
Give it a list of the different content types on your site — blog, store, member area, and so on — and it walks through how to configure a robots.txt file so crawl budget goes toward the pages that should rank. It also covers how often to revisit the file and what events (new sections, migrations, indexing problems) should trigger an update, which is useful when nobody on the team owns robots.txt maintenance.
Starting point for keyword research before you have any other data — specify a main category, how many topics you want, and how many table columns to spread them across, and it returns a table of semantically distinct seed keywords under that niche. The example in the prompt uses 'gym exercise' with 30 topics across 5 columns as a working default if you're unsure what numbers to pick.
Takes raw analytics data for a given time period, along with business context and the stakeholder audience, and converts it into a client-ready business narrative rather than a metrics dump. Output covers a three-sentence executive summary, key business wins, revenue and traffic impact, market position, ROI demonstration, next steps, and suggested visuals — swap in the actual stakeholder (CMO versus founder) since the framing shifts a lot.
Turns an existing outline into a full, publish-ready blog draft written to a specific voice and length. - Inputs: niche, target word count, article title, outline, brand voice notes, competitor blog links - Expands every subheading into full copy in one pass - Follow-up step suggests where to place images or infographics - Last step in the seed keyword to outline to intro to draft chain
Drafts the opening paragraphs of a blog post from just a topic, a target keyword, and a word limit, returning two versions — one that previews what the article covers, and one that opens by naming the problem the topic solves. A follow-up step then proposes a thesis statement pulled from whichever introduction you pick, so the rest of the article has something concrete to build around.
Give it an article title and the URL of your blog's index page, and it drafts a sequential, SEO-aware outline that structures the post from introduction through conclusion. A follow-up prompt then suggests three internal links from your existing blog posts to work naturally into the new article — feed the resulting outline straight into the SEO blog content expander to draft the full post.
Feed in your own SEO metrics, a named competitor's metrics, and market context, and it builds a side-by-side SWOT matrix covering technical SEO, content quality, backlink profiles, keyword rankings, and organic visibility for both sides. The output pairs the matrix with five prioritized strategic recommendations and an implementation plan, so it's only as sharp as the real numbers you feed into strengths and weaknesses.
Recommends a clean, SEO-friendly URL slug for a new article from just its working title. - Input: article title or topic only - Suggests a structured slug rather than a raw title dump - Follow-up explains why the structure helps both SEO and usability - Still expects you to trim the slug to essential keywords yourself
Give it an already-written article's topic and its target keyword, and it drafts one SEO-optimized meta description that follows length and best-practice conventions, then a follow-up step generates three more variations to choose from. Best used when a page is missing a description entirely or the existing one isn't earning clicks — for a rewrite that also accounts for competitor snippets, use the meta title and description rewriter instead.
Takes an already-approved SEO strategy document, the target C-suite audience, desired presentation length, and business priorities, then reframes it as a slide deck built around outcomes instead of tactics. Returns a slide-by-slide outline — title, key message, supporting data, visual recommendation, and speaker notes for each slide — so strip out tactic-level detail before pasting the strategy in, since the prompt handles the reframing itself.
Fixes a single underperforming or over-length title tag rather than generating a full batch of options. - Inputs: blog post topic and current title tag's character count - Returns one revised, length-compliant title tag - Follow-up explains the SEO reasoning behind the change - For multiple angles instead of one fix, use the intent-based title generator
Compares two SERP snapshots for the same target keyword pulled at different points in time and surfaces every meaningful position change — domains that moved three or more spots, new entrants to the top 10, drop-offs, and any shift in SERP features like snippets or People Also Ask. The output closes with strategic implications and recommended actions, making it the prompt to run right after a suspected algorithm update to separate real signal from ranking noise.
Feed in a target keyword, the top 10 current SERP results (titles, descriptions, URLs, formats), and optional context on your brand or audience, and it reverse-engineers exactly what Google is rewarding for that query right now. Returns primary and secondary search intent with justification, the page elements and content format required to compete, opportunities to win SERP features like featured snippets or PAA boxes, and E-E-A-T differentiators — especially valuable on YMYL topics.
Maps out where CTAs should sit across a landing page's user journey based on just a conversion goal — sign-ups, purchases, demo requests — and the page's topic, replacing scattered guesswork with a placement rationale tied to how a visitor actually moves through the page. A follow-up step then suggests the text and design elements that make each placed CTA more effective, and it pairs well with a CTA copy or form-friction prompt once positions are locked in.
Builds a full year of content planning from an industry, target audience, business goals, and known seasonal trends, mapping each of the 12 months to a theme, three content pillars, five key topics, seasonal tie-ins, relevant industry events, and recommended content types. Meant to be revisited quarterly, swapping in real performance data as each quarter closes so the calendar stays grounded instead of becoming a one-time planning exercise.
Feed in an aging article's full body text and, optionally, its live URL, and a model with web-browsing verifies every time-sensitive claim against current sources while checking today's SERP intent and format against what the page currently delivers. It returns one clear decision — update, new page, merge, or no action — with a before/after list of outdated facts and citations, a 0-10 cannibalization risk score with subscores, an implementation plan, and top risks, so it requires live browsing access to work as designed.
Walks through building an XML sitemap that reflects real page hierarchy and priority rather than a flat list of URLs. - Inputs: business/site description, website link, and list of pages - Explains how hierarchy and priority should be structured - Follow-up generates an embeddable XML sitemap for WordPress - For large sites, paste pages in batches by category instead of all at once
Generates a structured batch of email subject lines for testing, grouped by psychological angle rather than random variation. - Inputs: email topic, audience, main message, desired action, brand voice, and words to avoid - Produces: 20 subject lines grouped by angle, preview text for the 5 strongest, and a testing hypothesis per group - Flags: spam-risk wording and recommends one A/B test pair to run first - Built for email marketers who want a defensible reason behind every subject line, not just volume
Paste a draft agent skill or reusable prompt along with your project context, the target task, available tools, and known risks, and get back a structured audit covering purpose, required inputs, output format, safety boundaries, and failure modes. The review also flags missing checks and repeatability gaps, then returns an improved version ready to test — useful before wiring a skill into an autonomous coding agent or handing it to a team.
Submit a proposal along with your project context, stack, constraints, and team's skill level to get a skeptical second opinion before committing engineering weeks to it. The review separates what's genuinely strong from what's over-engineered, surfaces hidden coupling that will resurface later as maintenance cost, and ends with a clear verdict plus a minimal implementation path instead of just a list of concerns.
Paste a diff along with your public API surface, schema context, and configuration context to get a structured audit of breaking changes before you ship a release. It checks renamed methods, changed signatures, request or response field changes, unmigrated schema changes, environment variable renames, and altered defaults, then returns a severity-ranked table with affected users, migration paths, and a deprecation strategy where one is needed.
Feed in a stack trace, expected versus actual behavior, the relevant code, environment, recent changes, and what you've already tried when you can't tell which layer is actually failing. Returns ranked hypotheses weighed with evidence for and against each one, a step-by-step debugging plan, and both a quick fix and a proper fix so you can unblock now while scheduling the real solution.
Paste code along with its purpose, stack, module, and constraints to get a full-spectrum review covering correctness, security, performance, maintainability, error handling, accessibility, and test coverage in one pass. Returns a severity-ranked issues table, the top 3 priorities, positive observations, and specific tests to add — built to run right before merging a PR or handing code to a peer reviewer.
Give it a raw feature idea along with product context, target users, technical stack, and constraints, and get back more than a task list. It clarifies the problem statement, surfaces assumptions and open research questions, scopes an MVP with explicit out-of-scope items, then works through user stories, technical design, data model needs, implementation phases, and risks before ending with a validation plan.
Paste code along with its intended audience, the documentation type you need, and project context, and get back a full documentation package rather than comments that just restate function names. Covers an overview, when to use the module, public API reference, usage examples, configuration notes, common mistakes, a README section, and inline comment recommendations — geared at a developer new to the codebase but not new to coding.
Turns a raw diff and a short context note into a PR description reviewers can actually use, grounded in the real file and function names pulled from the diff rather than generic phrasing. Outputs a three-bullet what/why/risk summary, testing notes, the files that most deserve attention, migration or compatibility concerns, and a suggested PR title — and says so if the diff is too large to summarize well.
Turns a messy file or module you want to clean up into a step-by-step refactoring plan, built around your stated goal, available tests, and time budget rather than a full rewrite. Each step comes with a risk level and a way to verify it before moving on, plus tests to add, a rollback plan, and an explicit list of what not to touch yet. Meant for code that already works but is getting harder to change safely.
Reviews code that touches auth, user input, file handling, or payments, using the data it handles and its auth model as context for a targeted rather than generic pass. Returns a severity-ranked findings table, a plain-language exploit scenario for each issue, a concrete fix, a safer pattern to use instead, and tests to add. Strictly defensive: it won't write exploit code, only flag and remediate.
Generates a full test suite for a pasted code block, matched to your stated framework, test type, and existing test style so the output fits straight into the project. Delivers a test plan table, happy-path and edge-case tests, error-case tests, mock setup for external dependencies, realistic test data, and a list of remaining coverage gaps — plus the runnable test code itself.
Generates five distinct X (Twitter) thread ideas built around a single {topic}, each one paired with a strong opening-tweet hook meant to stop the scroll and pull readers into the full thread. Useful for copywriters, founders, and social media managers who want a shortlist of angles to choose from before investing time writing out a complete thread. Pairs well with a follow-up prompt that expands the winning idea into a full benefit-driven structure.
Produces 20 platform-native social post ideas tailored to one platform, niche, audience segment, and goal. - Inputs: platform, niche, audience, goal, brand voice, topics to include and avoid - Each idea includes a title, hook, format, main point, CTA, and why it fits the platform - Mixes promotional and non-promotional posts, with at least 5 low-effort options - Useful for seeding the first batch of a content calendar
Takes a detailed offer brief — the offer name, the problem it solves, its format, two descriptions of the target audience, their primary and secondary wants, what they want to avoid, and four differentiating benefits — and turns it into ten distinct value proposition options. Each option comes with a punchy one-line statement, a short follow-up line of supporting marketing copy, and an explanation of how that angle positions the offer against competitors. Built for landing pages, headlines, and ad copy where a single confident line needs to do a lot of work.
Brainstorms five Instagram Reels concepts designed for viral potential, built around a specific {target_audience} and the {product_or_brand} to feature. Each concept is a starting point rather than a finished script, meant to be validated against trending audio, formats, and current platform behavior before filming begins. Useful for planning a content batch when you need several concepts to test rather than committing to one idea upfront.
Generates a full pre-writing outline for a long-form article, turning a topic, primary keyword, audience, user problem, desired outcome, and content depth into a ready-to-draft structure. The output includes an H1, introduction angle, a nested H2/H3 outline with key points and examples per section, a FAQ block, and suggested internal links and external references to verify. Built for writers who want the SEO skeleton locked down before they start typing, without forcing keywords into every heading.
Maps internal linking opportunities across a set of static content pages using the current page, a list of available pages, the target audience, and the site's overall goal. It returns which pages should link to the current one, which pages the current one should link out to, recommended anchor text that avoids repetition, a breadcrumb suggestion, a related-prompts section, and topic/tag improvements. Built for static sites where links are generated at build time and navigation should come before SEO.
Feed in a page title, summary, primary and secondary keywords, audience, search intent, and brand name, and get back ten meta title options and ten meta description options weighed against click-through value and intent match, plus one recommended pairing with the reasoning behind it. Built for Astro pages and prompt-library detail pages where the result maps directly into frontmatter or an SEO component.
Acts as a pre-publish SEO gate for a prompt-library page, scoring frontmatter and body content before it goes live. - Inputs: page frontmatter, page content, target keyword, audience - Checks title clarity, meta description quality, heading structure, and search intent match - Flags thin-content risk and missing examples or inputs - Outputs a 1-10 score, an issues table, fixes, and rewritten frontmatter
Analyzes one keyword against your audience and business context to decide what kind of page should actually be built for it. - Inputs: keyword, audience, business context, existing page idea - Classifies primary and secondary search intent plus funnel stage - Recommends page format (guide, list, landing page, comparison) and required sections - Flags what to leave out and where the conversion opportunity sits
Takes a topic, primary and secondary keywords, audience, search intent, competitor notes, and a business goal, then produces a full content brief rather than just an outline. Covers search intent summary, recommended page type, H1, H2/H3 structure, keyword usage notes, questions to answer, internal and external link ideas, a draft meta title and description, and a content quality checklist — built for search pages, tag pages, and individual prompt-library entries.
Builds a four-email activation sequence for users of a given {product} who signed up but never completed the {activation_action}, targeting a specified {audience} and addressing their likely {blockers}. Each email is built to resolve one blocker at a time and points toward the {value_moment}, and the output includes subject lines, preview text, body copy, a CTA, trigger timing, and suppression rules per email. Suited to SaaS products, tools, and any account-based service with a clear activation step to recover.
Writes a personalized cold email to a specific {recipient_role} at a given {company}, built around a relevant {trigger} or observation, the {problem} it solves, and a concrete {proof_point}. Returns five subject line options, three email variants under 120 words each, one follow-up email, personalization notes, and a note on what additional recipient information would make the email stronger. Recipient and company details should always be verified before sending, since the rules explicitly forbid inventing facts about the recipient.
Plans a single newsletter issue for a given {audience} around one {topic} and {main_message}, rather than a scattered list of links. - Inputs: audience, topic, main message, links or resources, offer/CTA, tone, length - Output: subject line and preview text options, an opening paragraph, a section outline, link placement notes, a CTA section, and a plain-text version - Keeps the issue built around one main idea with no filler intro - Suited to recurring publications like weekly product or content updates
Creates a full welcome email sequence for new subscribers of a given {business}, based on how they joined (such as a lead magnet or signup), a specific {offer}, and an {end_goal} for the relationship. Each email returns its own goal, subject line, preview text, body copy, CTA, personalization idea, and a spam/risk note, with rules that prioritize building trust before selling. A five-email sequence is a reasonable default length if the {sequence_length} input isn't already decided.
Paste in a paragraph along with its academic field, audience, purpose, and citation style, and this prompt returns a tightened version alongside an explanation of the structural changes it made. It also flags which claims still need a citation, which terms need defining, and suggests a transition sentence to connect the paragraph to what comes before or after.
Give this prompt a topic and it writes a detailed, save-worthy checklist formatted for Pinterest. Each item is phrased as a single, clear action rather than a bundled task, so the list is easy to scan, easy to follow, and worth pinning for later reference.
Supply the platform, offer, audience, campaign goal, benefit, objections, proof points, compliance limits, and tone, and this prompt builds a full set of ad copy variants for split-testing. - 5 short headline options - 5 primary text variations - 3 CTA options across different urgency levels - 3 distinct copy angles - A table mapping each variation to the audience segment it fits best
Feed in your offer, target audience, main problem, benefit, proof points, price point, tone, and preferred CTA, and this prompt drafts a complete AIDA sales page: five headline options for attention, a problem-focused opening for interest, benefit-driven copy with objections handled for desire, and five CTA variants at different urgency levels for action, plus a list of any assumptions it made along the way.
Enter a topic your audience is weighing up, and this prompt writes a Facebook post that lays out both the pros and cons honestly rather than pushing a single angle. It's built for niches where readers are wary of overtly promotional content, using a balanced, informative tone to earn trust and help people make their own informed choice.
Give this prompt a project or event to feature and it writes a behind-the-scenes Facebook post. - Shares interesting details that outsiders wouldn't normally see - Frames the audience as insiders getting early or exclusive access - Works best paired with real photos or short video clips rather than text alone - Suited to product launches, events, or ongoing projects
Give this prompt a topic, target audience, and website URL, and it structures a full X (Twitter) thread built entirely around benefits. It opens with an attention-grabbing intro tweet, dedicates one tweet to each individual benefit, and closes with a CTA tweet driving traffic to your site — feed in your actual benefit list beforehand for tweets tied to real product facts rather than generic claims.
Give this prompt a product name and its distinct benefits, and it writes four sales page bullet points for the benefits section. - Each bullet spotlights exactly one unique benefit - Works best when you already have a list of distinct benefits to feed in - Ready to drop straight into a sales page layout - Keeps the tone punchy and scannable rather than descriptive
Feed in your business name, industry, audience, core offer, values, competitors, preferred tone, and words to avoid, and this prompt builds a full brand messaging system in one pass. The output covers a voice summary, do/don't tone rules, messaging pillars, a one-sentence positioning statement, 10 tagline options, and ready-to-adapt examples for website hero copy, social bios, and email intros, plus a checklist for keeping future copy consistent.
Feed in a set of bullet points and this prompt expands them into a full X (Twitter) thread written entirely in Russian, turning each key point into its own engaging tweet. Since tone and idiom can drift in generated translations, have a native or fluent Russian speaker review the thread before you post it rather than publishing the output as-is.
Paste in text along with the intended audience, tone, reading level, and purpose, and this prompt returns not one but three rewrites: a clarified full version, a shorter version, and a bullet-point version. It also explains what changed and why, and flags any parts of the original that stayed unclear even after editing — useful for tightening emails, documentation, or landing page copy.
Paste in a batch of comments or DMs along with your brand voice, audience, reply goal, and any sensitive limits, and this prompt drafts response options for each one. - A short reply, a warmer reply, and a helpful reply with a follow-up question per comment - Flags which comments carry risk and need human review before responding - Keeps replies human-sounding rather than templated - Never promises support actions you haven't already authorized
Give this prompt a product name and its details, and it writes a short, confident product description that highlights the key features and benefits in a clear, scannable way. It's built for quick product page or marketplace listing copy rather than long-form sales pages — for a more detailed, multi-part rewrite, pair it with the Product Description Benefit Rewriter prompt instead.
Feed in one long source piece — an article, video, podcast, or documentation page — along with its original format, target platforms, audience, goal, and tone. This prompt breaks it into 10 social posts, 5 short video ideas, 3 email newsletter angles, 5 quote cards, and 3 carousel outlines, plus a republishing schedule, while flagging which assets still need visuals.
Give this prompt a topic relevant to your brand and it writes an engaging poll question with two or more answer options. - Delivers a conversational Facebook/Instagram version with a relevant hashtag - Delivers a separate, more professional LinkedIn-toned variant of the same poll - Nudges followers to vote and share their reasoning in the comments - Works best kept to 2-4 answer options for higher response rates
Paste in raw post-sale survey responses, form answers, or reviews, and this prompt mines that voice-of-customer data for the three biggest motivations that pushed people to buy, the main doubts they had beforehand, and the surprising upsides they discovered afterward. It closes with concrete takeaways for strengthening your marketing messages, and works best run on a batch of responses collected right after purchase rather than a single comment.
Give this prompt a product or service and it spotlights a customer's success story or testimonial as a Facebook post. It blends narrative text with room for visuals into a single compelling post — feed it a real customer quote or story as source material rather than letting it invent one from scratch.
Give this prompt a customer, the problem they faced, and the product or service they used, and it drafts a short success story outline. - Identifies the turning point in the customer's situation - Explains what specifically worked - States the concrete result they achieved - Works best fed real customer details rather than invented ones
Give this prompt a product or service and it writes a Facebook post explaining how folding it into a daily routine makes a real difference, opening with a hook in the first sentence and keeping an upbeat tone throughout. It's especially suited to habit-forming categories like wellness, fitness, or productivity tools where everyday, repeated use is the actual selling point.
Give this prompt a topic and it shares five lesser-known, interesting facts about it, formatted as a run of "Did You Know?" posts for Pinterest. Each fact is written to be both educational and pinnable — fact-check anything surprising or specific before publishing, since the model can get details wrong.
Describe your dream life a set number of years from now, and this two-part prompt first tells a vision-casting story of a day as your future self, then builds a concrete weekly and daily schedule to get you there. - Takes a timeframe and a detailed dream-life description across life domains - Factors in your working style and schedule constraints - Produces a narrative day-in-the-life piece - Follows up with an actionable weekly/daily routine
Give this prompt a topic and it sets up a LinkedIn poll built around a relevant, thought-provoking question for your network. It supplies a few answer options plus an accompanying post explaining why the question matters and inviting people to vote and comment — keep the options to 2-4 and mutually exclusive for the best response rate.
Paste in an excerpt from a blog post, article, or transcript along with your target audience, and this prompt repurposes it into a full X (Twitter) thread. - Opens with a hook tweet built to grab attention - Breaks the material into concise, engaging body tweets - Closes with a CTA tweet driving interaction or traffic to your site - Works best on source content that already has a clear narrative or argument
Give this prompt your brand and event details, and it writes a teaser Facebook post that drops exciting details about an upcoming event while deliberately leaving room for a follow-up post series. Plan those follow-ups as a short campaign rather than a one-off, so the teaser has somewhere to go and builds anticipation over multiple posts.
Feed in a single offer and get five distinct, professional-tone call-to-action variations built to drive clicks, each varying its urgency and phrasing so you have real contrast for A/B testing. Useful for marketers who need quick CTA options for ads, emails, or landing pages without starting from scratch on every test.
Generates five short, clear email subject lines for a single campaign, built around the campaign topic and the specific action you want the reader to take next. Useful for marketers drafting a new send who want several ready-to-compare options rather than committing to the first line that comes to mind. Test a few against each other before locking in the winner.
Produces a value-first LinkedIn post built around five practical, audience-useful tips on any topic you supply, closing with a question designed to spark comments and crowdsource more tips from others. Works best as a structural template you fill with your own real expertise rather than a source of facts.
Rewrites a flat draft of social or marketing copy into five distinct versions engineered to spark curiosity and discussion. - Input: the original draft copy that needs sharper angles - Output: 5 alternate versions, each built to provoke thought and debate - Considers what stirs curiosity, prompts replies, and invites people to share opinions - Useful when a scheduled post feels flat and needs a stronger discussion hook - Compare all five against your brand voice before picking the most provocative one
Takes a weak or underperforming opening line for an X (Twitter) thread and rewrites it into five alternative hooks, each engineered to grab attention and pull readers into the rest of the thread. Best used when a thread's first line isn't landing in testing. Try the strongest option as a standalone tweet too, since a hook that reads well in context can still fall flat on its own.
Announces a giveaway for a named product or service, laying out the prize, entry rules (like/follow/tag steps), and a winner announcement date in an enthusiastic tone with hashtags. Produces two matching versions from the same inputs: one for Facebook and Instagram, and a more professional variant for LinkedIn. Check your platform's promotion rules before publishing either one.
Reviews a full draft against its audience, goal, tone target, and publishing channel, then delivers direct coaching-style feedback instead of generic encouragement. Covers what works, what fails, where readers will get confused, which sentences to cut, a stronger structure recommendation, and a rewritten version of the weakest section. Best used on important pages before they go live.
Builds a full opening-line toolkit for a single post idea, generating 10 hook options, 3 caption versions, and 5 CTA variations based on the platform, audience, their pain or desire, tone, and target length you supply, plus an explanation of which hook is strongest. Useful for A/B testing a post before it goes live, especially when the idea is solid but the opening line feels weak.
Drafts a blog post introduction built to hook the reader within the first three lines. - Inputs: the blog post's topic and its target audience - Output: a short intro paragraph with a strong opening hook - Keeps tone clear and reader-focused throughout - Good for a fast first draft; tighten the hook further on competitive topics
Writes five inspirational Instagram caption options for a given topic and audience, each opening with an attention-grabbing hook and staying under 100 words. Useful when a post needs an uplifting, shareable caption but you want several openings to compare. Pick the option whose hook best matches the accompanying image or video rather than the strongest line in isolation.
Creates an interactive quiz post around a chosen topic, built from a set of engaging questions meant to entertain and inform your audience while inviting them to share their results in the comments. Designed for comment-driving engagement content on Facebook; keep the quiz short since long quizzes see much lower completion in a feed format.
Builds a structured A/B testing plan for improving a landing page's conversion rate. - Inputs: primary visitor goal, secondary goal, page areas to focus testing on, and optional KPIs - Output: a testing plan covering headlines, layout, CTAs, and other named elements - Suggests KPIs to track per test - Suited for evergreen funnels and pages you plan to keep tuning rather than treat as one-off
Generates a complete landing page draft from your offer, audience, pain point, unique value proposition, proof points, and top objections, covering hero headline, problem, solution, benefit blocks, how-it-works, social proof, an objection-handling FAQ, final CTA, and meta title/description. Meant as copy content to plug into a design, not a finished page — real testimonials and numbers still need to be verified before publishing.
Produces a fast, eye-catching headline-and-CTA pairing for a landing page, built around the specific offer and unique selling point you provide. Pair it with the Landing Page Copy Blueprint prompt when you need full page copy rather than just the top section.
Announces an upcoming webinar, conference, or industry event, explaining why it's worth attending and encouraging your network to join, based on the industry and event details you supply. Also prompts a natural follow-up recap post covering insights and takeaways after the event happens. Plan both posts at the same time so the recap actually gets written.
Writes a LinkedIn post that names a common challenge in a given industry, proposes possible solutions, and asks your network to share their own experiences overcoming it. Positions you as a problem-solver in your field; naming a specific, real challenge rather than a vague one is what drives replies on this format.
Drafts a LinkedIn post offering your viewpoint on current trends in a given industry. - Input: the industry to cover - Output: a post with trend insights and a closing discussion prompt - Points out how the trends affect professionals in your network - Add 2-3 real trend details you actually want to comment on — a fully generic version won't spark discussion
Writes a professional-tone LinkedIn post promoting a named product, structured around one value point, one pain point, and one call to action. Keep the pain point specific and relatable rather than vague, since generic pain points read poorly on this platform. Suited for quick product-promotion posts aimed at a professional audience.
Turns a product or service win into a LinkedIn narrative post, walking through the journey and results and spotlighting the key lessons meant to inspire and inform your audience. Works as a structure for telling a true story — feed in the real journey and results rather than treating it as a source of facts.
Generates three short, shareable motivational quotes for Instagram Stories. - Inputs: your target audience and the action you want to inspire in them - Output: 3 quotes, each under 30 words, with an upbeat tone - Written from a social-media-marketing-expert persona - Pair each quote with a simple background graphic rather than posting as plain text
Announces a new product launch with platform-matched copy for Facebook, Instagram, and LinkedIn in one pass, built from the product name, its key feature or benefit, a buy link, and, for the LinkedIn version, the problem it solves. Adds excitement-driven language and launch hashtags automatically. Swap in hashtags relevant to your own niche rather than using the examples verbatim.
Writes a TikTok video script structured as myth, then fact, repeated for each common misconception about a given topic, aiming for an educational tone that still stays entertaining. Always verify the facts the model supplies before filming, since myth-busting content is especially risky to get wrong.
Writes a direct-response social post that pushes followers toward a specific action, spelling out the benefits of acting and adding urgency where it genuinely fits, with a direct link included. Produces one version for Facebook/Instagram and a professional LinkedIn variant from the same inputs — the desired action, product or service, and link. Only add urgency phrasing if it's actually true, since false urgency erodes trust.
Writes a casual, low-effort social post built around a playful question, joke, or challenge tied to a given topic, meant to pull followers into commenting. Produces a Facebook/Instagram version and a separate LinkedIn variant from the same topic input. Match the humor level to your brand voice, since LinkedIn tolerates less silliness than Facebook or Instagram.
Turns existing content — a blog post, script, or newsletter — into 15 sharp, non-generic interview questions, written from the perspective of a curious, journalistic-style podcast host addressing a given audience and newsworthy angle. Useful both for generating new content ideas from your own material and for rehearsing answers before a real interview.
Builds a thank you page from your audience details, the offer that led to it, your primary objectives, and what the audience expects post-conversion, folding in the right elements — a data-collection survey, registration confirmation steps, or download links — for your specific scenario. Also adds general engagement elements like social share prompts, testimonials, and cross-promotion. Trim the scenario sections down to the one that matches your page's actual purpose before running it.
Feed in a current product description along with the product name, audience, main use case, feature list, benefits, tone, and length limit, and this prompt rewrites the copy so it sells outcomes instead of specs. It returns a short product-card blurb, a full page description, five benefit-led bullets, three headline options, and a plain-English explainer for non-technical buyers, all without inventing unsupported claims.
Turn one topic into a batch of bite-sized tips built for Pinterest's scan-and-save format. - Input: a single topic you want tips about - Output: a set of short, standalone tips, one idea each - Best for: quick-reference pins that work without extra context - Tip: keep each idea narrow enough to fit on one pin
Paste in a LinkedIn story or post you've already published and this prompt reshapes it into a more conversational, personal version tuned for a Facebook audience. It strips away professional framing that plays well on LinkedIn but falls flat elsewhere, adjusting pacing and tone so the same core story fits Facebook's more casual, comment-friendly feed.
Build a scenario-driven teaching video from a subject, audience, common mistake, and desired learning outcome. - Inputs: subject, audience, scenario context, skill being taught, common mistake, learning outcome, target length - Structure: scenario setup, decision point, viewer question, wrong-path and correct-path explanations - Output: full narration script plus reflection questions and an optional quiz - Best for: instructional or training videos built around a realistic decision
Paste a full video script along with its audience, goal, target length, and tone, and this prompt audits it the way a YouTube retention editor would — flagging a weak hook, slow or redundant sections, missing context, shaky transitions, unclear claims, and CTA placement. It follows up with prioritized fixes, a rewritten hook, sample rewritten transitions, and a shortened version of the script if the pacing calls for it.
Describe the product or topic shown in a photo along with the target audience, and this prompt generates five distinct one-to-two-sentence Instagram captions, each paired with relevant hashtags to help the post get discovered. It's built for single-image posts that need a punchy, scroll-stopping line rather than a long caption.
Turn any simple, 3-to-5-step process tied to a topic into a short TikTok voiceover script. Give it just the topic, and it writes a clear, step-by-step walkthrough scripted for spoken delivery — sized for a quick how-to video rather than a longer tutorial format.
Build a full posting calendar for a specific platform instead of a scattered list of one-off content ideas. Feed in your brand, platform, audience, goal, content pillars, posting cadence, campaign period, and any offers running, and the prompt maps out each post's date, pillar, format, hook, core idea, CTA, suggested visual, and success metric — balanced across educational, trust-building, and conversion content.
Turn a product or service into a plain-language, step-by-step how-to post for Facebook. - Input: the product or service being demonstrated - Format: numbered steps written in simple, visual-friendly language - Output: a how-to guide meant to be paired with real photos or screenshots - Best for: showing a product in action rather than describing it abstractly
Name the goal someone is trying to reach, and this prompt maps out a clear, numbered process for getting there, written in the concise, save-for-later style that works on Pinterest. It keeps each step simple enough to skim at a glance, aiming for a manageable 5-to-8-step guide people will actually pin and revisit rather than a long, dense tutorial.
Paste in a raw customer quote and this prompt rewords it into a tighter, punchier line suited for a website testimonial section, without changing what the customer actually said. It's a polish pass rather than an invention pass, aimed at making real feedback read as compellingly on the page as it sounded when the customer said it.
Unsure whether a piece of copy should read as formal, casual, persuasive, or educational? Feed in the text, audience, goal, and channel. The prompt returns five distinct tonal rewrites — professional, friendly, persuasive, educational, and short-and-direct — then recommends the best fit for your goal, explains why, and offers a hybrid version if none of the five lands perfectly.
Stake out a clear point of view on a current issue in your field instead of posting another neutral take. Give this prompt a trending topic and it drafts an opinion piece that states a viewpoint, backs it with data or examples, and closes by inviting readers to weigh in — just verify any stats or examples before publishing, since they're placeholders for real sourcing.
Get a quick starting set of Google Ads copy to test, built around a product's strongest selling points. - Inputs: product name and key benefits to highlight - Output: 3 distinct ad copy variants, each with its own CTA - Tone: direct and benefit-first - Reminder: check character limits and ad policy compliance before launching
Give this prompt a single topic and it writes a fast-paced TikTok script built around your top five actionable tips on that subject, with each tip kept short enough to fit one sentence of spoken script. It's designed for the quick-cut pacing TikTok viewers expect, so the audience can follow and apply each tip without slowing the video down.
When a product is hard to explain or the homepage headline sounds like every competitor's, this prompt takes what you do, who you serve, the problem you solve, your differentiator, your proof points, and your main alternatives, and turns them into a one-sentence UVP, a short website paragraph, a 30-second elevator pitch, five headline options, a differentiator table, and a list of proof you should still collect.
Kick off a community content challenge that gets your audience posting photos or videos of your product. - Input: the product or service to feature in the challenge - Output: an announcement post inviting entries with a prize call-out - Tone: exciting and community-building - Prep step: lock in the prize and entry rules before generating the post
For when you have a video title but no real structure yet — this expands a rough idea into a full outline, not a finished script. Provide the title, audience, core problem, promise, points to cover, available examples, and tone, and it returns a hook angle, open loop, detailed section-by-section outline, expected viewer takeaways per section, evidence needed, transition notes, retention risks, and CTA placement.
Feed in a writing sample that represents the voice you want, along with a separate piece of target text that needs rewriting, plus the audience, purpose, and specific things to preserve or avoid. The prompt analyzes the sample's style patterns, rewrites the target text to match, and hands back five style rules plus notes on any spots where the target text couldn't fully match the source voice — useful whenever multiple pages need to sound like the same author.
Combine an audience poll with supporting context in a single X (Twitter) thread. - Input: the topic the poll asks about - Structure: intro tweet, poll tweet, supporting-facts tweets, closing vote-and-share tweet - Best for: driving engagement through a question rather than a straight statement - Tip: keep the poll question simple and binary for a higher response rate
Give this prompt the product or service you want to showcase, and it builds an X (Twitter) thread around three separate user stories or testimonials, each written as a compelling mini-narrative that highlights a real benefit or positive experience. It closes with a tweet inviting others to share their own stories — feed in actual customer quotes rather than letting the draft invent testimonials from scratch.
Built for educational or commentary videos where structure and retention decide whether viewers stay past the first minute. Supply the title, audience, main promise, key points, examples, desired length, tone, and CTA, and the prompt returns a 10-second hook, a reason-to-keep-watching intro, a section-by-section outline, a full narration script, pattern interrupts, visual and B-roll suggestions, and a closing CTA.
Generate five different vertical short-video script options built around one core takeaway. - Inputs: topic, audience, main takeaway, style, target length in seconds, CTA - Each option includes: first-line hook, timestamped script, on-screen text, visual direction, CTA, and why the hook works - Format: fast-paced, immediate payoff, no long setup - Best for: YouTube Shorts, Reels, or TikTok scripts needing rapid iteration
Turns a broad, pasted research topic into a structured question map that separates core questions from background questions, lists assumptions that still need validating, names the likely source types to consult, and lays out a practical research sequence to follow. Flags which claims will require primary sources rather than secondary summaries. Best used at the very start of an open-ended research project, before committing time to any one direction, to scope an unfamiliar subject with a clear path instead of unfocused reading.
Condense a long document — meeting notes, a research report, an internal memo — into something a busy reader can act on fast. - Input: the full document text - Output: a 3-sentence TL;DR plus key points, decisions, risks, and open questions - Bonus: action items with owners pulled out when they're mentioned - Best for: skimming long material without losing what actually needs follow-up
Paste in any paragraph that's accurate but bloated — a product blurb, an email, a slice of documentation — and this prompt tightens it without losing meaning, nuance, or voice. It strips filler words, simplifies convoluted sentence structure, and returns one polished rewrite alongside a short list of the specific edits made, so you can see exactly what changed and why.
Turns one keyword and a short note on site context into a full writing brief: target reader, search intent, an H2/H3 heading structure, key points for each section, internal link opportunities, and an FAQ list drawn from likely reader questions. Meant for handing straight to a writer so the structure is locked in before a single paragraph gets drafted, cutting down on thin or unfocused sections.
Turns a single seed keyword into an organized set of content clusters instead of a flat keyword dump, grouping related queries by search intent. For each cluster it suggests one primary page to target, lists supporting article ideas, and flags whether the opportunity is commercial or informational, so you can slot the output straight into an editorial calendar. Just supply the seed keyword and a short description of your audience.
Turns a short page summary and one target keyword into five ready-to-use SEO snippet options. - Inputs: page summary and primary keyword only - Titles capped at 60 characters, descriptions at 155 - Matches search intent instead of leaning on clickbait phrasing - Suited to new landing pages or refreshing stale metadata fast
Paste a diff to get a fast, senior-engineer-style pass that prioritizes what actually matters — correctness bugs, regressions, security issues, missing tests, and maintainability risks — over style nitpicks. Each finding comes with severity, evidence pulled directly from the diff, and a concrete suggested change, making it a solid gate to run before opening a pull request.
Takes a single function plus its test framework (or "unknown" if you're not sure) and writes a practical test suite covering the main happy path, boundary cases, invalid inputs, and expected failure modes. It matches the project's existing test style when one is visible in the pasted context, and states any assumptions it made before showing the actual test code.
Feed in a suspicious snippet along with the error message and expected behavior, and get back a ranked list of likely bugs instead of a vague hunch. Each finding names the observable symptom, the probable root cause, the exact lines or functions responsible, and a concrete fix to apply. When the pasted context isn't enough to be confident, it says exactly what extra detail is missing instead of guessing at a diagnosis.
Paste any unfamiliar snippet and get a statement-by-statement walkthrough instead of a single high-level summary. Each line is explained in plain language: what it does, why it's there, and any assumption it quietly depends on, with jargon defined inline as it comes up. Built for developers who already know how to code but are new to this particular codebase, library, or language idiom.