What is geo:optimize?

A command that improves a local Markdown or HTML content file for GEO, meaning better visibility in generative search and answer systems. It preserves the file's frontmatter, such as title or metadata settings.

Use it to analyze, rewrite, add suitable markup to, and export a local Markdown or HTML file into an optimized output folder.

It gives you a quicker way to analyze and improve one content file without running a full audit. It also keeps the original metadata attached to the result.

geo:optimize — Command for Claude Code by mverab/eGEOagents

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo

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

agentmods

npx agentmods add commands/mverab/egeoagents/geo-optimize

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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/mverab/egeoagents/geo-optimize/github.svg)](https://agentmods.dev/commands/mverab/egeoagents/geo-optimize)

Your own site

<a href="https://agentmods.dev/commands/mverab/egeoagents/geo-optimize"><img src="https://agentmods.dev/badge/commands/mverab/egeoagents/geo-optimize/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.

Your own site · 80×15

<a href="https://agentmods.dev/commands/mverab/egeoagents/geo-optimize"><img src="https://agentmods.dev/badge/commands/mverab/egeoagents/geo-optimize.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 15 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 409 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.

Model	Per session	Once invoked
Fable 5.1	$0.00015	$0.00409
Opus 5.5	$0.00006	$0.00164
Sonnet 5.5	$0.00003	$0.00082
Haiku 4.5	$0.00002	$0.00041

Measured 1mo ago against content hash e435aa59fd4a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

geo:optimize 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 1mo 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-optimize.md · 41 lines

What it actually says

/geo:optimize Command

Quick optimization of local content files.

Workflow

Validate MCPs - Run validation-doctor; if missing, provide setup snippets
Frontmatter Extraction - If the input file contains frontmatter (YAML block between --- or TOML block between +++), extract and preserve this block completely. Do not pass the frontmatter to the analyzer or rewriter agents. Only pass the content body.
Analyze - Read and score the content body (source of truth)
Rewrite - Apply GEO optimization to the content body based on analyzer output
Schema - Generate appropriate markup based on analyzer output
Reassemble & Export - Output the optimized version to the geo-output/optimized/ directory:
- markdown: Reassemble the file by prepending the original, unmodified frontmatter to the optimized content body. Save as [name].md.
- html: Convert the optimized content body to HTML (preserving all headers, tables, lists, and formatting). Insert the original frontmatter properties into appropriate HTML metadata tags (<meta> or structured header) inside a clean, modern HTML document template. Save as [name].html.

Output

Optimized content (with frontmatter preserved or converted to HTML metadata)
Schema markup if applicable
Change summary with impact estimates

Example Usage

/geo:optimize ./content/homepage.md
/geo:optimize ./content/homepage.md html
/geo:optimize ./blog/new-post.md markdown

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.

1mo ago First seen · 41 lines · 15 tokens per session scan A e435aa59fd4a

Subscribe to this mod's changes

geo:optimize is a command published in the GitHub repository mverab/eGEOagents (207 stars, last pushed 2d ago), licensed MIT. It adds 15 tokens to every session and 409 once invoked, about $0.0001 per session on Opus 5.5. 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.

Marketing and SEO aeo ai-search-optimization content-optimization generative-engine-optimization geo schema-markup

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

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

social

Run an organic-social (ECHO) workflow: channel portfolio and voice dossiers, platform-native content and calendars, the social-quality gate with a pre-publish go/no-go, community/inbox/crisis operations, and the listening/SOV/dark-social measurement loop. Not sure? Use /aaron-marketing:auto.