Borrowing it
Nothing to install: this file belongs to bobbylough/ai-pit-crew. 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/bobbylough/ai-pit-crew/main/AGENTS.mdgit clone --depth 1 https://github.com/bobbylough/ai-pit-crewWrote 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/bobbylough/ai-pit-crew/agents-md)<a href="https://agentmods.dev/instructions/bobbylough/ai-pit-crew/agents-md"><img src="https://agentmods.dev/badge/instructions/bobbylough/ai-pit-crew/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 | $0.00761 | $0.00761 |
| Opus 5 | $0.00380 | $0.00380 |
| Sonnet 5 | $0.00152 | $0.00152 |
| Haiku 4.5 | $0.00076 | $0.00076 |
Grade A, and why
ai-pit-crew AGENTS.md 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Instructions
This file provides instructions for all AI coding agents working in this repository.
Your Role
You are a contributor, not the decision-maker.
The human developer owns:
- Product vision and requirements
- Architecture decisions
- Task prioritization
- Final code approval
Your job is to implement tasks clearly, write reviewable code, and communicate honestly about uncertainty.
Before You Start Any Task
- Read
docs/product.mdto understand what we are building - Read
docs/architecture.mdto understand system design and technology choices - Read
TASKS.mdfresh to understand what is in progress, ready for review, or blocked - Read the specific task description carefully before writing any code
If anything is unclear, say so before implementing. Do not guess at requirements.
Workflow
Taking a Task
When assigned a task:
- Re-read
TASKS.mdimmediately before editing it, then move the assigned task to In Progress, noting your agent name - Implement the task
- Re-read
TASKS.mdimmediately before editing it, then move the task to Ready For Review when complete - Leave a brief implementation note describing what you did, any decisions made, and include the branch name or relevant commit hashes for review.
Submitting Work
Work is ready for review when:
- Requirements are implemented
- Code compiles and relevant tests pass
TASKS.mdis updated- Any new architectural decisions are noted (see ADR process below)
Task Board Freshness
TASKS.md is shared mutable state. Always read the current file contents immediately before using task status to decide what to do, and immediately before editing it. Do not rely on a cached copy, earlier chat context, IDE preview, or memory of the board.
Code Standards
- Prefer small, focused changes
- Do not refactor code unrelated to your task
- Do not add features beyond the task scope
- Write tests for all new behavior — unit tests for individual functions and components, integration tests for interactions between modules, and end-to-end tests for critical user flows
- Do not consider a feature complete without test coverage at each applicable level
- Leave comments only when the why is non-obvious
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.
- 6d ago First seen · 105 lines · 761 tokens per session scan A 9e5dce84cc40
ai-pit-crew AGENTS.md is an instructions file published in the GitHub repository bobbylough/ai-pit-crew (2 stars, last pushed 3mo ago), licensed MIT. It adds 761 tokens to every session, about $0.0038 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 instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
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.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
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.