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 Infrasity-Labs/dev-gtm-claude-skills --skill blog-geogit clone --depth 1 https://github.com/Infrasity-Labs/dev-gtm-claude-skillsWrote 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/infrasity-labs/dev-gtm-claude-skills/blog-geo)<a href="https://agentmods.dev/skills/infrasity-labs/dev-gtm-claude-skills/blog-geo"><img src="https://agentmods.dev/badge/skills/infrasity-labs/dev-gtm-claude-skills/blog-geo/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/infrasity-labs/dev-gtm-claude-skills/blog-geo"><img src="https://agentmods.dev/badge/skills/infrasity-labs/dev-gtm-claude-skills/blog-geo.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00148 | $0.02314 |
| Opus 5 | $0.00074 | $0.01157 |
| Sonnet 5 | $0.00030 | $0.00463 |
| Haiku 4.5 | $0.00015 | $0.00231 |
Grade A, and why
blog-geo 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 9d 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 — 271 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Blog GEO: AI Citation Optimization Audit
Scores blog posts for AI citation readiness across ChatGPT, Perplexity, and Google AI Overviews. Generates citation capsules and a 0-100 AI Citation Readiness score with platform-specific recommendations.
Cross-reference
This skill covers FLOW surface 3 (AI assistant citations: ChatGPT, Perplexity, Claude, Gemini, Copilot, You.com) and contributes to surface 2 (SERP plus AI Overviews). Surface mapping: skills/blog/references/flow-alignment.md.
For directly relevant AI-citation prompts (AI-supporting-pages-rewrite-prompt, ai-detector-test, ChatGPT discovery, visibility prompts), see /blog flow optimize.
Key Research Data
Reference these benchmarks throughout the audit:
- Only 11% of domains cited by both ChatGPT and Perplexity (Digital Bloom, domain-level)
- 80% of LLM citations don't rank in Google's top 100 (Ahrefs)
- Brands 6.5x more likely cited through third-party sources (AirOps)
- 120-180 word sections get 70% more ChatGPT citations (SE Ranking, Nov 2025)
- Comparison tables with
<thead>achieve 47% higher AI citation rates (directional) - Content freshness: 76.4% of top citations updated within 30 days (Ahrefs, ~17M citations)
Audit Process
Step 1: Read Content
Extract from the blog post:
- Full content text and word count
- Heading structure (H1, H2, H3 hierarchy)
- Individual paragraphs and their word counts
- FAQ sections (if present)
- Schema markup (JSON-LD, microdata, RDFa)
- robots.txt mentions or meta robots directives
- Any TL;DR or summary boxes
- Comparison tables and their HTML structure
- Numbered/ordered lists
- Definition-style formatting
Step 2: Passage-Level Citability (4 pts)
Check each section between headings for AI-extractable passages:
| Check | Criteria |
|---|---|
| Word count | Each section contains 120-180 word self-contained passages |
| Context independence | Each passage makes sense extracted from surrounding context |
| Claim structure | Passages contain: specific claim + supporting evidence + source attribution |
| Completeness | Passage answers a question without requiring reader to read adjacent sections |
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.
- 9d ago First seen · 271 lines · 148 tokens per session scan A 675eca38f094
blog-geo is a skill published in the GitHub repository Infrasity-Labs/dev-gtm-claude-skills (124 stars, last pushed 2mo ago), licensed MIT. It adds 148 tokens to every session and 2,314 once invoked, about $0.0007 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 2026-09-03.
Other skills, from other repositories
geo-audit
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geo
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agent-readiness-scan
Use when a client audit, GEO/AI-visibility snapshot, or remediation re-scan needs the Cloudflare agent-readiness score from isitagentready.com — e.g. Theo client audits, "is the site agent-ready", markdown negotiation / MCP / llms.txt / Content-Signal checks, or tracking score deltas after Tier 0/1 fixes.
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