geo-report-pdf

geo-report-pdf is a skill for Codex from bytefer/geo-seo-codex. It costs 65 tokens per session (1,700 once invoked), scanned A, original, MIT.

A report generator that turns a GEO audit written in Markdown into a styled PDF. GEO, or Generative Engine Optimization, concerns how easily AI search tools can find and describe a business.

In plain words
What is it for?
Use it after a GEO audit to create a PDF with a cover page, score tables, tagged findings, and a 90-day improvement roadmap.
Why use it?
It removes the manual work of formatting audit results into a client-ready document. It also avoids writing extra code to build score tables and finding labels.

Skill for Codex

Written for Codex: reads ~/.codex or $CODEX_HOME. Also seen: mentions Codex; $skill-name invocation.

Good fit Use it after a GEO audit to create a PDF with a cover page, score tables, tagged findings, and a 90-day improvement roadmap.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/bytefer/geo-seo-codex/geo-report-pdf
Install

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.

Any agent
npx skills add bytefer/geo-seo-codex --skill geo-report-pdf
Clone the repo
git clone --depth 1 https://github.com/bytefer/geo-seo-codex

Made for: Codex.

Wrote 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.

agentmods badge for geo-report-pdf

README.md
[![agentmods](https://agentmods.dev/badge/skills/bytefer/geo-seo-codex/geo-report-pdf/github.svg)](https://agentmods.dev/skills/bytefer/geo-seo-codex/geo-report-pdf)
Your own site
<a href="https://agentmods.dev/skills/bytefer/geo-seo-codex/geo-report-pdf"><img src="https://agentmods.dev/badge/skills/bytefer/geo-seo-codex/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.

agentmods 80×15 button for geo-report-pdf

Your own site · 80×15
<a href="https://agentmods.dev/skills/bytefer/geo-seo-codex/geo-report-pdf"><img src="https://agentmods.dev/badge/skills/bytefer/geo-seo-codex/geo-report-pdf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,700 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00065 $0.01700
Opus 5 $0.00032 $0.00850
Sonnet 5 $0.00013 $0.00340
Haiku 4.5 $0.00006 $0.00170

Measured 10d ago against content hash ae22db5851c0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

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 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.

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.

skills/geo-report-pdf/SKILL.md · 152 lines

How it starts

The opening of the file, as written. The whole thing — 152 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 — install through Homebrew, Chocolatey, Scoop, apt, or your platform package manager
  • Chrome/Chromium-compatible browser — Google Chrome, Microsoft Edge, Chromium, or Brave

No Python dependencies. No ReportLab. No JSON data wrangling.

How It Works

  1. Read GEO-AUDIT-REPORT.md in the current directory (created by $geo-audit)
  2. Extract cover metadata from the report (brand name, domain, GEO score, date, locations)
  3. Run pandoc with the bundled CSS + HTML template to produce a self-contained GEO-REPORT.html
  4. Run a Chrome/Chromium-compatible browser in headless mode to print the HTML to GEO-REPORT.pdf

Resolve GEO_ROOT from CODEX_GEO_ROOT, the loaded plugin/repository root, or the classic installer path ${CODEX_HOME:-$HOME/.codex}/skills/geo. The pandoc template ($GEO_ROOT/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

GEO_ROOT="${CODEX_GEO_ROOT:-}"
if [ -z "$GEO_ROOT" ]; then
  for candidate in "$PWD" "$PWD/.." "$PWD/../.." "${CODEX_SKILLS_DIR:-${CODEX_HOME:-$HOME/.codex}/skills}/geo"; do
    if [ -f "$candidate/templates/geo-report-template.html" ]; then
      GEO_ROOT="$candidate"
      break
    fi
  done
fi
if [ -z "$GEO_ROOT" ]; then
  echo "GEO runtime root not found. Set CODEX_GEO_ROOT to the geo-seo-codex plugin/repo root."
  exit 1
fi

pandoc GEO-AUDIT-REPORT.md \
  --to html5 \
  --standalone \
  --embed-resources \
  --template "$GEO_ROOT/templates/geo-report-template.html" \
  --css "$GEO_ROOT/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

Read the full file on GitHub · 152 lines

Changes

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.

  1. 10d ago First seen · 152 lines · 65 tokens per session scan A ae22db5851c0

Subscribe to this mod's changes

geo-report-pdf is a skill published in the GitHub repository bytefer/geo-seo-codex (11 stars, last pushed 2mo ago), licensed MIT. It adds 65 tokens to every session and 1,700 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.

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