Borrowing it
Nothing to install: this file belongs to Auriti-Labs/geo-optimizer-skill. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Auriti-Labs/geo-optimizer-skill/main/AGENTS.mdgit clone --depth 1 https://github.com/Auriti-Labs/geo-optimizer-skillWrote 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.
[](https://agentmods.dev/instructions/auriti-labs/geo-optimizer-skill/agents-md)<a href="https://agentmods.dev/instructions/auriti-labs/geo-optimizer-skill/agents-md"><img src="https://agentmods.dev/badge/instructions/auriti-labs/geo-optimizer-skill/agents-md.svg" alt="Measured on agentmods" height="20"></a>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 | $0.01506 | $0.01506 |
| Opus 5 | $0.00753 | $0.00753 |
| Sonnet 5 | $0.00301 | $0.00301 |
| Haiku 4.5 | $0.00151 | $0.00151 |
Grade A, and why
geo-optimizer-skill AGENTS.md scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
2. Do not introduce direct `requests.get()` or equivalent on unvalidated user input. How it starts
The opening of the file, as written. The whole thing — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Project Context
GEO Optimizer is an open-source Python toolkit for Generative Engine Optimization. It audits and improves websites so they are more discoverable and citable by AI search engines such as ChatGPT, Perplexity, Claude, and Gemini.
Current project shape:
- Python package with CLI commands, core audit/fix logic, FastAPI web demo, and MCP server support
- MIT licensed
- Python 3.9+ compatibility is required
Primary user-facing surfaces:
geo auditgeo fixgeo llmsgeo schemageo-web
Repository Map
Top-level structure:
src/geo_optimizer/cli/: Click presentation layer and output formatterssrc/geo_optimizer/core/: business logic, scoring, audit execution, fix generationsrc/geo_optimizer/models/: dataclasses and centralized config/constantssrc/geo_optimizer/utils/: HTTP, validation, cache, parserssrc/geo_optimizer/web/: FastAPI app, badge generation, web entrypointssrc/geo_optimizer/mcp/: MCP server tools/resourcessrc/geo_optimizer/i18n/: translationstests/: pytest suite, mostly mocked end-to-end and unit coverage
Important file roles:
models/config.py: centralized constants, scoring weights, schema templates, bot listsmodels/results.py: result dataclassescore/audit.py: full audit orchestrationutils/http.py: secure fetching, anti-SSRF, response size protectionsutils/validators.py: public URL and safe-path validation
Architectural Rules
These are hard constraints:
-
core/must never print or directly format output. Return dataclasses frommodels/results.py. -
Keep CLI and formatter logic in
cli/.cli/*can call core and format results; core must not depend on CLI. -
Keep constants centralized. Do not hardcode scoring weights, AI bot lists, or schema defaults outside
models/config.py. -
Preserve Python 3.9 compatibility. Every Python file under
src/must include:from __future__ import annotationsAlso avoid relying on Python 3.10+ only behavior, including newer
entry_points()assumptions.
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.
- 8d ago First seen · 195 lines · 1,506 tokens per session scan A 7b901c12aab7
geo-optimizer-skill AGENTS.md is an instructions file published in the GitHub repository Auriti-Labs/geo-optimizer-skill (773 stars, last pushed 2d ago), licensed MIT. It adds 1,506 tokens to every session, about $0.0075 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
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AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
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spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.