Individual skill
aeo-score-audit
Use this skill when an AI-visibility score needs to be trusted, explained, or challenged — "why did our AEO score drop," "prove this visibility number to the client," "this scan result looks wrong." Traces any aggregate visibility or sentiment score down to the individual scans behind it, and from there to the raw AI answer text — an audit trail from headline number to evidence.
skills/yahav-fuchs/aeo-score-audit/SKILL.md
Source commit 5d786aad0c7b2ca59b1abf1f601f9407ca261996
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- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- Yes
- Observed behavior
- Instructions only
- Last checked
- Nov 11, 2026
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- Repository stars (not skill ratings)
- 237
- Repository last updated
- Oct 20, 2026
- License
- MIT
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- security Derived category
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SKILL.mdcore · 2,788 bytes
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Use when a visibility score moves unexpectedly, a client wants receipts, or a scan result looks off. Produces an audit trail: aggregate → contributing scans → raw AI answers. Never explain a score movement from the aggregate alone — decompose first.
## The three-step drill
1. **aggregate** — pull the top-level number: visibility percentage, mention count, total scans, average sentiment for the period
2. **decompose** — explain the score into its component scan results: which scans registered a brand mention and which didn't. Score drops usually localize here — one engine, one country, or one topic did the damage, not "the brand"
3. **inspect** — for any surprising scan, pull the full record: the raw AI answer text, every extracted field, every citation found. This is where "we lost visibility" becomes "engine X stopped citing the comparison page for prompt Y"
## Check the methodology version
Every result carries an analysis version. Before reading a long-term trend, confirm the version is consistent across the window — a methodology change explains a score shift that has nothing to do with the brand's actual standing. Version-boundary comparisons are the classic false alarm.
## What the audit is for
