Borrowing it
Nothing to install: this file belongs to fenjo26/OpenGSC. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/fenjo26/OpenGSC/main/.agents/skills/aeo-visibility-review/SKILL.mdgit clone --depth 1 https://github.com/fenjo26/OpenGSCWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/fenjo26/opengsc/aeo-visibility-review)<a href="https://agentmods.dev/skills/fenjo26/opengsc/aeo-visibility-review"><img src="https://agentmods.dev/badge/skills/fenjo26/opengsc/aeo-visibility-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/fenjo26/opengsc/aeo-visibility-review"><img src="https://agentmods.dev/badge/skills/fenjo26/opengsc/aeo-visibility-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00048 | $0.00574 |
| Opus 5 | $0.00024 | $0.00287 |
| Sonnet 5 | $0.00010 | $0.00115 |
| Haiku 4.5 | $0.00005 | $0.00057 |
Grade A, and why
aeo-visibility-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 43 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenGSC AEO Visibility Review
Goal
Tell the user where they stand in AI search: which tracked questions cite/mention their site per engine, where they're invisible, and what content or authority signals would most plausibly change that.
Required inputs
- The site (domain). Call
list_sitesif unknown.
OpenGSC MCP tools
get_aeo_visibility: tracked questions with the latest per-engine cited/not-cited state. Engines using live web search (ChatGPT, Perplexity) signal citation; Claude/Grok signal brand mention.get_search_performance(dimension=query): questions people already find the site with in Google — candidates to add to AEO tracking.get_striking_distance: pages close to page 1 often correlate with citability — sources AI search tends to pick up.get_geo_audits: stored GEO audit reports. Where AEO tracks the same questions over time, these are one-off deep audits of a single query — they name which competitors AI search cited and why, which is the "what does a citable source look like here" evidence the scoreboard lacks.fetch_page_content: pull a page that did get cited and read what makes it quotable — direct answers up top, named entities, data points, visible dates.
Workflow
- Pull
get_aeo_visibility. Build a per-engine scoreboard: cited / not cited / never checked. - Classify the losses: invisible everywhere (content gap) vs cited by search-grounded engines only (authority/mention gap) vs mentioned but not cited (formatting/source-quality gap).
- Cross-reference with
get_search_performance: strong Google queries with zero AI citations are the highest-leverage fixes — the content already ranks, it needs to become quotable (clear answers, data points, named entities, updated dates). - Suggest 3–5 new questions worth tracking, phrased the way real users ask assistants.
Output format
- Scoreboard table: question × engine (✓ cited / ✗ not / — unchecked).
- Diagnosis per losing question (one line each).
- Prioritized fixes: content changes first, then authority plays.
- Suggested new questions to track.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 43 lines · 48 tokens per session scan A 733b0131a9d8
aeo-visibility-review is a skill published in the GitHub repository fenjo26/OpenGSC (22 stars, last pushed yesterday), licensed MIT. It adds 48 tokens to every session and 574 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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