Publisher: Corey Haines · Editorial profile by AI Tools Ratings · Review method
What task is this skill designed for?
Audit one public product page for questions a buyer needs answered, then design a repeatable citation observation log.
What input and output should you expect?
Input: Rendered page text, current primary-source facts, intended audience and five fixed buyer questions. Include baseline answers only if actually collected.
Output: A proposed fact correction list, self-contained answer sections and a measurement plan distinguishing mentions, citations and recommendations.
What does it need to run?
Use a browsing-capable client for current platform guidance. Inspect the bundled reference relevant to the task; agent-readiness and answer-accuracy are separate workflows. Optional tracking services are not prerequisites for a document-only review.
The pinned publisher README declares support for Agent Skills clients including Claude Code, Codex and Cursor. Compatibility follows the publisher’s stated support.
How should you approach installation?
- Inspect the pinned SKILL.md, license and referenced files needed for your specific task before installation.
- Follow the publisher README for your actual Agent Skills client.
- Try the illustrative prompt with synthetic material in a separate workspace. Review the checklist and approve any publishing, account or external-message action separately.
Installation guide: discovery, dependencies and runtime checks
What files, accounts or data can it access?
Reads pages and supplied answer logs. Connected search or monitoring services may receive the brand, prompts and URLs; keep private launch plans out of public queries. Editing crawler settings or publishing content requires separate review.
What does the skill cost?
MIT-licensed source. Agent subscriptions, model usage and optional research or analytics services have separate costs.
What are its limits and alternatives?
Source heuristics and observational studies do not guarantee citations. A mention is not a referral, and a citation is not a recommendation. No original AI visibility experiment was run for this profile.
Use SEO Audit for crawl and conventional search issues; choose this workflow when answer accuracy or AI-source traceability is the concrete problem.
What could you ask in a small trial?
Try this with a small sample:
Audit this synthetic pricing page against the attached price table. Write two answer sections without new claims. Propose five fixed questions and a dated observation log; do not invent baseline visibility or predicted uplift.
How would you verify the result?
- Verify every rewritten price and limit against the supplied source.
- Separate missing evidence from a confirmed error.
- Keep engine, date, prompt and observed answer in the measurement log.
Use a baseline and record acceptance evidence before treating a successful task as a reliable workflow.
Which source and license were checked?
Read the reviewed SKILL.md at its pinned commit · Complete reviewed folder
Repository and current publisher guidance
Checked:
MIT — identified in the repository LICENSE at the pinned commit. External services and dependencies have their own terms. License evidence
Version details and review scope
Source: coreyhaines31/marketingskills/skills/ai-seo
Reviewed commit: e85f3cbc2e4a79bf33b2a12e9bdd9087d414735b
SKILL.md SHA-256: 1293062b48cecc0a19f0e5444ecd0c929f640171fbbb234d44812dbd01cb8a52
Source-document review. This profile covers the source workflow, stated dependencies and license evidence. See our editorial methodology for how we distinguish source reviews and hands-on evaluations.