geo-seo-claude is a Claude Code skill for improving how websites appear in AI-powered search while retaining traditional search-engine optimization. It is used by marketers and website practitioners for analysis such as citation scoring, crawler review, authority assessment, structured data, and platform-specific recommendations. The catalogue entries are skills and agents that carry out this optimization workflow.
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 zubair-trabzada/geo-seo-claude --skill geo-report-pdfgit clone --depth 1 https://github.com/zubair-trabzada/geo-seo-claudeWrote 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/zubair-trabzada/geo-seo-claude/geo-report-pdf)<a href="https://agentmods.dev/skills/zubair-trabzada/geo-seo-claude/geo-report-pdf"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/geo-seo-claude/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/zubair-trabzada/geo-seo-claude/geo-report-pdf"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/geo-seo-claude/geo-report-pdf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- 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 7 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 | $0.00059 | $0.01334 |
| Opus 5 | $0.00030 | $0.00667 |
| Sonnet 5 | $0.00012 | $0.00267 |
| Haiku 4.5 | $0.00006 | $0.00133 |
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 13d 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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GEO PDF Report Generator (pandoc pipeline)
Prerequisites
- pandoc —
brew install pandoc - Google Chrome — must be installed at
/Applications/Google Chrome.app/
No Python dependencies. No ReportLab. No JSON data wrangling.
How It Works
- Read
GEO-AUDIT-REPORT.mdin the current directory (created by/geo audit) - Extract cover metadata from the report (brand name, domain, GEO score, date, locations)
- Run
pandocwith the bundled CSS + HTML template to produce a self-containedGEO-REPORT.html - Run Chrome headless to print the HTML to
GEO-REPORT.pdf
The pandoc template (~/.claude/skills/geo/templates/geo-report-template.html) injects:
- A full-bleed dark navy cover section with the GEO score badge
- Per-section cover metadata (date, business type, locations, platform)
- JavaScript that runs inside Chrome before printing to color-code score cells and severity-tag finding sections
Workflow
Step 1: Check for audit report
Look for GEO-AUDIT-REPORT.md in the current directory. If absent, tell the user to run /geo audit <url> first.
Step 2: Extract cover metadata from the report
Read the top of GEO-AUDIT-REPORT.md and extract:
| Field | Where to find it |
|---|---|
brand_name |
First H1 title (after "GEO Audit Report:") |
domain |
Second bold line (e.g. **Domain:** alexamediasolutions.com) |
geo_score |
Line matching ## Overall GEO Score: XX / 100 |
score_label |
Word after the score on that same line (e.g. "Poor", "Fair", "Good") |
date |
**Audit Date:** line |
business_type |
**Business Type:** line |
locations |
**Locations:** line |
platform |
**CMS:** line |
Step 3: Run pandoc
pandoc GEO-AUDIT-REPORT.md \
--to html5 \
--standalone \
--embed-resources \
--template ~/.claude/skills/geo/templates/geo-report-template.html \
--css ~/.claude/skills/geo/templates/geo-report-style.css \
--metadata title="GEO Audit Report — <brand_name>" \
--metadata brand_name="<brand_name>" \
--metadata domain="<domain>" \
--metadata geo_score="<geo_score>" \
--metadata score_label="<score_label>" \
--metadata date="<date>" \
--metadata business_type="<business_type>" \
--metadata locations="<locations>" \
--metadata platform="<platform>" \
-o GEO-REPORT.html
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.
- 13d ago First seen · 121 lines · 59 tokens per session scan A 9990a6a1b8be
geo-report-pdf is a skill published in the GitHub repository zubair-trabzada/geo-seo-claude (10,540 stars, last pushed yesterday), licensed MIT. It adds 59 tokens to every session and 1,334 once invoked, about $0.0003 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.
Other skills, from other repositories
geo-report-pdf
Generate a professional PDF report from a GEO audit using pandoc + Chrome headless. Converts GEO-AUDIT-REPORT.md into a styled, client-ready PDF with a cover page, color-coded score tables, severity-tagged findings, and a 90-day roadmap.
geo-report-pdf
Generate a professional PDF report from GEO audit data using ReportLab. Creates a polished, client-ready PDF with score gauges, bar charts, platform readiness visualizations, color-coded tables, and prioritized action plans.
geo-report-pdf
Generate a professional PDF report from GEO audit data using ReportLab. Creates a polished, client-ready PDF with score gauges, bar charts, platform readiness visualizations, color-coded tables, and prioritized action plans.
realestate-report-pdf
Professional PDF Property Report Generator — compiles all PROPERTY-.md analysis files into a polished, client-ready PDF with score gauges, comparison tables, financial projections, and investment recommendations.
literature
Load when extracting GEO accessions, dataset metadata, and downloadable references from a scientific paper (PDF / URL / DOI / PubMed ID / raw text) for downstream omics analysis. Skip when the dataset is already in hand; only routing a query (use orchestrator).
visibly-seo-pdf-build
Build a clean, brand-compliant PDF from an analysis or offer. Use when the user asks to generate, render, or export a client-ready PDF presentation or document with their corporate identity — cover page, header/footer, section bars, tables, ROI boxes.