Audit answer visibility
Skill kimsanguine/signal-to-growth/skills/audit-answer-visibility
Evidence-driven skills that turn customer signals into measurable growth.
npx -y skills add kimsanguine/signal-to-growth --skill audit-answer-visibilityAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- 12 days oldThe repository was created 12 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
- 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
Audit how a page or product answer is discoverable and citable using dated observations, technical checks, and source-backed findings. Use when reviewing SEO, GEO, AEO, answer visibility, citation readiness, 검색 노출, or 생성형 검색 대응.
SKILL.md
2.3 KB, 400 tokens by cl100k_base, as published. Nobody here has run it
Audit Answer Visibility
Produce an evidence audit, not an invented probability of being cited. Separate live observation, inference, and recommendation.
Inputs
Require:
- target URLs or files;
- target audience, questions, locale, and competitors;
- observation date;
- access and authentication constraints;
- claim and source policy.
Use current authoritative sources when platform behavior may have changed.
Workflow
- Record the exact surface, date, locale, and access state.
- Check response status, canonical, robots, structured data, heading hierarchy, answer blocks, and cited sources.
- Test target questions only on surfaces the user authorized.
- Record what was directly observed without interpreting it.
- Add inference with confidence and alternative explanations.
- Add recommendations linked to observed gaps.
- Record inaccessible or unverified surfaces as unknown.
- If using a diagnostic score, expose weights and label the score as a heuristic.
Boundaries
- Let the model organize questions, gaps, and recommendations.
- Use deterministic checks for HTTP and markup facts where available.
- Require a person to interpret competitive importance and approve investment.
- Do not claim ranking, citation, or answer inclusion without a dated observation.
- Do not treat crawler accessibility as proof that an answer system used the page.
- Do not present a proprietary score as a calibrated probability.
Outputs
Create:
visibility-observations.jsonlcitation-gaps.mdtechnical-findings.mdrecommendations.md
Read references/output-contract.md before writing them.
Stop conditions
Stop when the target cannot be accessed, observation context is missing, a requested claim needs unavailable live verification, or a source cannot be attributed.
Verification
Confirm every finding has one of these states:
observedreportedinferredrecommendedunknown
Rerun time-sensitive observations before publication.