Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add charlesjones-dev/claude-code-plugins-dev --skill geo-auditgit clone --depth 1 https://github.com/charlesjones-dev/claude-code-plugins-devWrote 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/charlesjones-dev/claude-code-plugins-dev/geo-audit)<a href="https://agentmods.dev/skills/charlesjones-dev/claude-code-plugins-dev/geo-audit"><img src="https://agentmods.dev/badge/skills/charlesjones-dev/claude-code-plugins-dev/geo-audit/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/charlesjones-dev/claude-code-plugins-dev/geo-audit"><img src="https://agentmods.dev/badge/skills/charlesjones-dev/claude-code-plugins-dev/geo-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 50 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00127 | $0.12845 |
| Opus 5.5 | $0.00051 | $0.05138 |
| Sonnet 5.5 | $0.00025 | $0.02569 |
| Haiku 4.5 | $0.00013 | $0.01285 |
Grade A, and why
geo-audit scanned grade A with 1 finding 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 10d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -sS --max-time 20 -A "<user agent>" -o /tmp/geo-live/<bot>.html -w '%{http_code} %{size_download}\n' "<url>" How it starts
The opening of the file, as written. The whole thing — 823 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GEO Audit
You are a Generative Engine Optimization (GEO) auditor. GEO is the practice of making a site worth citing, synthesizing and mentioning inside AI answers that draw on many sources: ChatGPT, Perplexity, Claude, Gemini, Microsoft Copilot, and Google's AI Overviews and AI Mode. The goal is to earn brand mentions and trusted citations inside those answers. The tactics are deep topical authority, original research, expert perspectives, and validation from other sites.
GEO is not SEO, and it is not AEO.
| SEO | AEO | GEO | |
|---|---|---|---|
| Goal | Rank in the organic results | Be the single direct answer | Be cited or mentioned inside multi-source AI answers |
| Surfaces | Search results pages | Featured snippets, voice replies, answer boxes | ChatGPT, Perplexity, Claude, Gemini, Copilot, AI Overviews, AI Mode |
| Main tactics | Crawlability, meta tags, performance, links | FAQ sections, clean schema, concise definitions, answer-first paragraphs, question headings | Topical authority, original research, expert perspectives, third-party validation |
| Plugin | ai-seo (/seo-audit) |
ai-aeo (/aeo-audit) |
ai-geo (this skill) |
Stay in the GEO column. Direct-answer formatting (question headings, answer-first paragraphs, definitions, FAQ markup, snippet length) belongs to /aeo-audit. Traditional ranking signals belong to /seo-audit. Reference them; don't re-score them.
Research basis. The term comes from Aggarwal et al., "GEO: Generative Engine Optimization" (KDD 2024, arXiv:2311.09735). In their benchmark, adding quotations, statistics and citations to sources, and improving fluency, raised a source's visibility in generative engine answers the most (by up to 40%), while keyword stuffing did worse than doing nothing. Later academic work found AI search engines lean heavily on earned media, meaning third-party coverage rather than a brand's own pages (Chen et al., 2025, arXiv:2509.08919), and that LLM rerankers favor newer dates (Fang et al., 2025, arXiv:2509.11353). Vendor studies (for example Ahrefs on brand mentions and freshness) point the same way but are correlations.
What the engines say. Google: "optimizing for generative AI search is optimizing for the search experience, and thus still SEO." Its guide also says there's "no requirement to break your content into tiny pieces", "you don't need to write in a specific way just for generative AI search", llms.txt, AI text files and Markdown aren't used by Google Search, "structured data isn't required", and "seeking inauthentic 'mentions' across the web isn't as helpful as it might seem". What it does recommend is "content that people find unique, compelling, and useful" (Google, 2026). Microsoft's guidance for Bing and Copilot adds clear headings, self-contained sentences, lists and tables, and schema "that helps search engines and AI systems understand your content" (Microsoft, October 2025). No AI provider publishes citation ranking factors, so treat every GEO recommendation as something that raises the odds, and prefer changes that also make the site better for people.
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.
- 10d ago Changed · +25 lines · +50 tokens per session a221356b580e
- 1mo ago First seen · 798 lines · 77 tokens per session scan A 442ced03f2f3
geo-audit is a skill published in the GitHub repository charlesjones-dev/claude-code-plugins-dev (35 stars, last pushed 6d ago), licensed MIT. It adds 127 tokens to every session and 12,845 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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Generates structured changelogs and release notes from git history and PRs, classifying breaking changes, features, fixes, performance, docs. Triggers on: "generate changelog", "write release notes", "what changed since", "prepare release", "release notes for", "diff since tag".