geo-report

geo-report is a skill for Claude Code from zubair-trabzada/geo-seo-claude. It costs 28 tokens per session (4,257 once invoked), scanned A, original, MIT.

A report-writing tool that combines website checks about how well a business appears in AI-generated search answers. It turns scores and findings into one client-ready document.

In plain words
What is it for?
It helps create a GEO (generative engine optimization) readiness report from platform, structured-data, technical, and content audits, with optional checks for AI instructions and brand mentions.
Why use it?
It removes the need to gather separate audit results and explain technical issues yourself. Business owners and marketing leaders get prioritized actions in language they can use.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit It helps create a GEO (generative engine optimization) readiness report from platform, structured-data, technical, and content audits, with optional checks for AI instructions and brand mentions.

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Install with agentmods
npx agentmods add skills/zubair-trabzada/geo-seo-claude/geo-report
About the project

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.

zubair-trabzada/geo-seo-claude · 10,540 stars · on GitHub · skool.com

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 zubair-trabzada/geo-seo-claude --skill geo-report
Clone the repo
git clone --depth 1 https://github.com/zubair-trabzada/geo-seo-claude

Made for: Claude Code.

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

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/zubair-trabzada/geo-seo-claude/geo-report"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/geo-seo-claude/geo-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,257 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. Third-party audits
  • Socket pass 1 May 2026
  • Snyk pass 1 May 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00028 $0.04257
Opus 5 $0.00014 $0.02129
Sonnet 5 $0.00006 $0.00851
Haiku 4.5 $0.00003 $0.00426

Measured 13d ago against content hash 6c1c89648117, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

geo-report 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.

Origin

Copies of this mod

3 near-identical copies found in the catalogue:

skills/geo-report/SKILL.md · 400 lines

How it starts

The opening of the file, as written. The whole thing — 400 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GEO Client Report Generator

Purpose

This skill aggregates outputs from all GEO audit skills into a single, professional report that can be delivered directly to a client or stakeholder. The report is written for business owners and marketing leaders, not developers — technical findings are translated into business impact and clear action items with priority levels.

How to Use This Skill

  1. Run the following audits first (or use existing report data):
    • geo-platform-optimizer -> GEO-PLATFORM-OPTIMIZATION.md
    • geo-schema -> GEO-SCHEMA-REPORT.md
    • geo-technical -> GEO-TECHNICAL-AUDIT.md
    • geo-content -> GEO-CONTENT-ANALYSIS.md
    • (Optional) geo-llmstxt -> llms.txt assessment
    • (Optional) geo-brand-mentions -> brand authority data
  2. Collect all scores and findings
  3. Calculate the composite GEO Readiness Score
  4. Generate the client report using the template below
  5. Output: GEO-CLIENT-REPORT.md

GEO Readiness Score Calculation

Component Weights

Component Weight Source Skill
AI Platform Readiness 25% geo-platform-optimizer
Content Quality & E-E-A-T 25% geo-content
Technical Foundation 20% geo-technical
Schema & Structured Data 15% geo-schema
Brand Authority & Entity Presence 15% geo-platform-optimizer (entity signals)

Score Formula

GEO Score = (Platform Score * 0.25) + (Content Score * 0.25) + (Technical Score * 0.20) + (Schema Score * 0.15) + (Brand Score * 0.15)

Round to the nearest integer. Cap at 100.

Score Interpretation for Clients

Score Range Label Client-Facing Description
85-100 Excellent Your site is well-positioned for AI search. Focus on maintaining and expanding your advantage.
70-84 Good Solid foundation with clear opportunities to improve AI visibility. Targeted optimizations will yield significant results.
55-69 Moderate Your site has gaps in AI readiness that competitors may be exploiting. A structured optimization plan will close these gaps.
40-54 Below Average Significant barriers to AI search visibility exist. Without action, your brand risks being invisible in AI-generated answers.
0-39 Needs Attention Critical AI readiness issues require immediate action. Your competitors are likely capturing the AI search traffic your brand should own.

Read the full file on GitHub · 400 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. 13d ago First seen · 400 lines · 28 tokens per session scan A 6c1c89648117

Subscribe to this mod's changes

geo-report is a skill published in the GitHub repository zubair-trabzada/geo-seo-claude (10,540 stars, last pushed yesterday), licensed MIT. It adds 28 tokens to every session and 4,257 once invoked, about $0.0001 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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