geo:report

geo:report is a command for Claude Code from mverab/eGEOagents. It costs 12 tokens per session (214 once invoked), scanned A, original, MIT.

A command that gathers earlier GEO analysis files and turns them into a structured report. GEO means improving content so generative AI search systems can understand and recommend it.

In plain words
What is it for?
Creating an executive summary, score breakdown, before-and-after content comparisons, schema and metadata notes, and an implementation checklist.
Why use it?
It collects scores, findings, suggested content, and technical details in one report instead of leaving them across separate files.

Command for Claude Code

Written for Claude Code: arguments in frontmatter.

Good fit Creating an executive summary, score breakdown, before-and-after content comparisons, schema and metadata notes, and an implementation checklist.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/mverab/egeoagents/geo-report
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.

Clone the repo
git clone --depth 1 https://github.com/mverab/eGEOagents

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/commands/mverab/egeoagents/geo-report.svg)](https://agentmods.dev/commands/mverab/egeoagents/geo-report)
Your own site
<a href="https://agentmods.dev/commands/mverab/egeoagents/geo-report"><img src="https://agentmods.dev/badge/commands/mverab/egeoagents/geo-report.svg" alt="Measured on agentmods" height="20"></a>
Per session 12 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 214 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 $0.00012 $0.00214
Opus 5 $0.00006 $0.00107
Sonnet 5 $0.00002 $0.00043
Haiku 4.5 $0.00001 $0.00021

Measured 8d ago against content hash 96dd33c360a6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, 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 8d 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.

.claude/commands/geo-report.md · 55 lines

What it actually says

/geo:report Command

Compile a premium PDF-ready report from analysis data.

Workflow

  1. Gather - Collect data from geo-output/
  2. Compile - Create executive summary
  3. Format - Apply premium formatting
  4. Save - Output final report

Output

geo-output/report.md containing:

# GEO Optimization Report
Generated: [date]

## Executive Summary
- Overall Score: XX/100
- Estimated Ranking Improvement: +X positions
- Priority Actions: X items

## Score Breakdown
[Visual breakdown of all criteria]

## Content Analysis
[Detailed findings]

## Optimized Content
[Before/after comparisons]

## Technical Assets
[Schema markup, meta tags]

## Implementation Checklist
[Step-by-step action items]

## Appendix
[Raw data, methodology]

Example Usage

/geo:report
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. 8d ago First seen · 55 lines · 12 tokens per session scan A 96dd33c360a6

Subscribe to this mod's changes

geo:report is a command published in the GitHub repository mverab/eGEOagents (175 stars, last pushed 6d ago), licensed MIT. It adds 12 tokens to every session and 214 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.

Related

Other commands, from other repositories

seo-geo

SEO/GEO end-to-end along the SITE loop: survey demand and competitors, implement content, tune quality/tech/on-page, and evaluate authority/rankings/reports/memory (--phase survey|implement|tune|evaluate). Not sure? Use /aaron-marketing:auto.

aaron-he-zhu/aaron-marketing-skills · 58 tokens

ad

Run a paid-ads (ROAS) workflow: audience segments, account structure, ad creative, experiment design, pre-launch signal QA + the account-audit gate, measurement, and attribution. Not sure? Use /aaron-marketing:auto.

aaron-he-zhu/aaron-marketing-skills · 50 tokens

email

Run an email-marketing (SEND) workflow: deliverability/consent setup, segmentation, email creative, lifecycle flows, newsletter monetization, send-testing, and the email-quality audit gate. Not sure? Use /aaron-marketing:auto.

aaron-he-zhu/aaron-marketing-skills · 50 tokens

influencer

Run an influencer-marketing (STAR) workflow: audience & creator scouting, campaign targeting, briefs, outreach, amplification, and ROI reporting. Not sure? Use /aaron-marketing:auto.

aaron-he-zhu/aaron-marketing-skills · 39 tokens

launch

Run a product-launch (RAMP) workflow: positioning and launch tiering, window/early-access design, message house and asset kits, the launch-readiness gate with a T-1 go/no-go, launch-day execution, and the post-launch prove loop. Not sure? Use /aaron-marketing:auto.

aaron-he-zhu/aaron-marketing-skills · 64 tokens

narrative

Run a brand-narrative & messaging (TALE) workflow: trace the current message and positioning truth, architect the durable message house/voice/story canon, land it consistently across every surface, and evaluate resonance with tests and drift monitoring. Not sure? Use /aaron-marketing:auto.

aaron-he-zhu/aaron-marketing-skills · 59 tokens