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.