Borrowing it
Nothing to install: this file belongs to chankov/agent-fleet. 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/chankov/agent-fleet/main/AGENTS.mdgit clone --depth 1 https://github.com/chankov/agent-fleetWrote 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/chankov/agent-fleet/agents-md)<a href="https://agentmods.dev/instructions/chankov/agent-fleet/agents-md"><img src="https://agentmods.dev/badge/instructions/chankov/agent-fleet/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 | $0.01931 | $0.01931 |
| Opus 5 | $0.00966 | $0.00966 |
| Sonnet 5 | $0.00386 | $0.00386 |
| Haiku 4.5 | $0.00193 | $0.00193 |
Grade A, and why
agent-fleet 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 2d 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 — 209 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
This file provides guidance to AI coding agents working with code in this repository. pi is the coding agent Agent Fleet installs for; Claude Code takes part only as a coms peer (see docs/claude-code-coms-bridge.md).
Repository Overview
Agent Fleet — a Pi-centered multi-agent orchestration system (agent-hub dispatcher, herdr fleet control plane, coms peer messaging, Hermes remote control) plus a library of lifecycle skills and agent personas for pi. Skills live in two roots: fleet-native skills/ and the vendored upstream import vendor/agent-skills-upstream/skills/ (native wins on name collisions — see docs/UPSTREAM-SKILLS.md).
Skill-Driven Execution
Agent Fleet runs on a skill-driven execution model powered by this repository's /skills directory.
Core Rules
- If a task matches a skill, you MUST invoke it
- Skills are located in
skills/<skill-name>/SKILL.md - Never implement directly if a skill applies
- Always follow the skill instructions exactly (do not partially apply them)
Intent → Skill Mapping
The agent should automatically map user intent to skills:
- Feature / new functionality →
spec-driven-development, thenincremental-implementation,test-driven-development - Planning / breakdown →
planning-and-task-breakdown - Bug / failure / unexpected behavior →
debugging-and-error-recovery - Code review →
code-review-and-quality - Refactoring / simplification →
code-simplification - API or interface design →
api-and-interface-design - UI work →
frontend-ui-engineering
Lifecycle Mapping
The agent should internally follow this lifecycle and invoke the matching skill at each phase:
- DEFINE →
spec-driven-development - PLAN →
planning-and-task-breakdown - BUILD →
incremental-implementation+test-driven-development - VERIFY →
debugging-and-error-recovery - REVIEW →
code-review-and-quality - SHIP →
shipping-and-launch
This lifecycle is normally implicit — the agent maps user intent to the right skill without being asked.
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.
- 2d ago First seen · 209 lines · 1,931 tokens per session scan A 9be10a57ee1e
agent-fleet AGENTS.md is an instructions file published in the GitHub repository chankov/agent-fleet (14 stars, last pushed today), licensed MIT. It adds 1,931 tokens to every session, about $0.0097 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 2026-09-03.
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.