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 agentmods add commands/littlebearapps/pitchdocs/geogit clone --depth 1 https://github.com/littlebearapps/pitchdocsWhat 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 | $0.00012 | $0.00161 |
| Opus 5 | $0.00006 | $0.00081 |
| Sonnet 5 | $0.00002 | $0.00032 |
| Haiku 4.5 | $0.00001 | $0.00016 |
Grade A, and why
geo 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 3d 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.
What it actually says
/geo
Load the geo-optimisation skill for Generative Engine Optimisation patterns — citation capsules, crisp definitions, atomic sections, comparison tables, concrete statistics, and semantic scaffolding.
When to Use
- Optimising a README or guide for AI citation (ChatGPT, Perplexity, Google AI Overviews)
- Writing citation capsules for H2 sections
- Adding comparison tables for "X vs Y" queries
- Structuring docs for RAG extraction
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.
- 3d ago First seen · 22 lines · 12 tokens per session scan A 771ae6cbad60
geo is a command published in the GitHub repository littlebearapps/pitchdocs (7 stars, last pushed 3mo ago), licensed MIT. It adds 12 tokens to every session and 161 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 2026-08-31.
Other commands, from other repositories
create-skill
Create an AI skill from any source (URL, repo, PDF, video, notebook, etc.).
install-skill
One-command skill creation and packaging for a target platform.
sync-config
Sync a scraping config's URLs against the live documentation site.
review-renovate
Review and merge renovate PRs with automerge configuration updates.
plan-regression-tests
Plan regression tests for existing code with it.skip statements.
ado-pull
Pull latest changes from Azure DevOps (like git pull). Supports increment, project, or full living docs sync.