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 TheSmokeDev/geo-skills --skill geo-report-pdfgit clone --depth 1 https://github.com/TheSmokeDev/geo-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/thesmokedev/geo-skills/geo-report-pdf)<a href="https://agentmods.dev/skills/thesmokedev/geo-skills/geo-report-pdf"><img src="https://agentmods.dev/badge/skills/thesmokedev/geo-skills/geo-report-pdf/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/thesmokedev/geo-skills/geo-report-pdf"><img src="https://agentmods.dev/badge/skills/thesmokedev/geo-skills/geo-report-pdf.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 Rogue Agent · line 76 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00046 | $0.01579 |
| Opus 5 | $0.00023 | $0.00790 |
| Sonnet 5 | $0.00009 | $0.00316 |
| Haiku 4.5 | $0.00005 | $0.00158 |
Grade A, and why
geo-report-pdf 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- geo-report-pdf — 94% identical, 7 lines differ
- geo-report-pdf — 84% identical, 18 lines differ
How it starts
The opening of the file, as written. The whole thing — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GEO PDF Report Generator
Purpose
This skill generates a professional, visually polished PDF report from GEO audit data. The PDF includes score gauges, bar charts, platform readiness visualizations, color-coded tables, and a prioritized action plan — ready to deliver directly to clients.
Prerequisites
- ReportLab must be installed:
pip install reportlab - The PDF generation script is located at:
~/.claude/skills/geo/scripts/generate_pdf_report.py - Run a full GEO audit first (using
/geo-audit) to have data to include in the report
How to Generate a PDF Report
Step 1: Collect Audit Data
After running a full /geo-audit, collect all scores, findings, and recommendations into a JSON structure. The JSON data must follow this schema:
{
"url": "https://example.com",
"brand_name": "Example Company",
"date": "2026-02-18",
"geo_score": 65,
"scores": {
"ai_citability": 62,
"brand_authority": 78,
"content_eeat": 74,
"technical": 72,
"schema": 45,
"platform_optimization": 59
},
"platforms": {
"Google AI Overviews": 68,
"ChatGPT": 62,
"Perplexity": 55,
"Gemini": 60,
"Bing Copilot": 50
},
"executive_summary": "A 4-6 sentence summary of the audit findings...",
"findings": [
{
"severity": "critical",
"title": "Finding Title",
"description": "Description of the finding and its impact."
}
],
"quick_wins": [
"Action item 1",
"Action item 2"
],
"medium_term": [
"Action item 1",
"Action item 2"
],
"strategic": [
"Action item 1",
"Action item 2"
],
"crawler_access": {
"GPTBot": {"platform": "ChatGPT", "status": "Allowed", "recommendation": "Keep allowed"},
"ClaudeBot": {"platform": "Claude", "status": "Blocked", "recommendation": "Unblock for visibility"}
}
}
Step 2: Write JSON Data to a Temp File
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 · 165 lines · 46 tokens per session scan A c82890c212d0
geo-report-pdf is a skill published in the GitHub repository TheSmokeDev/geo-skills (22 stars, last pushed 9d ago), licensed MIT. It adds 46 tokens to every session and 1,579 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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