Borrowing it
Nothing to install: this file belongs to Smart-AI-Memory/attune-ai. 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/Smart-AI-Memory/attune-ai/main/AGENTS.mdgit clone --depth 1 https://github.com/Smart-AI-Memory/attune-aiWrote 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/smart-ai-memory/attune-ai/agents-md)<a href="https://agentmods.dev/instructions/smart-ai-memory/attune-ai/agents-md"><img src="https://agentmods.dev/badge/instructions/smart-ai-memory/attune-ai/agents-md/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.
<a href="https://agentmods.dev/instructions/smart-ai-memory/attune-ai/agents-md"><img src="https://agentmods.dev/badge/instructions/smart-ai-memory/attune-ai/agents-md.svg" alt="Reviewed on agentmods" width="80" 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 | $0.05809 | $0.05809 |
| Opus 5.5 | $0.02324 | $0.02324 |
| Sonnet 5.5 | $0.01162 | $0.01162 |
| Haiku 4.5 | $0.00581 | $0.00581 |
Grade A, and why
attune-ai 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 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.
How it starts
The opening of the file, as written. The whole thing — 482 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Attune AI
Project instructions for AI coding agents that do not read
.claude/ (Codex, etc.). Claude Code loads .claude/CLAUDE.md
instead. The shared, agent-agnostic core lives in
content/collaboration/contract.md and is projected into the
marked block below (and into .claude/CLAUDE.md) — edit the
master and re-run scripts/project_collaboration_contract.py,
never the block. Content outside the block is Codex-facing
orientation only.
Overview
Attune AI — AI-powered developer workflows with cost optimization
and multi-agent orchestration. Python 3.10+, published on PyPI as
attune-ai. Stack: pydantic, anthropic SDK / claude-agent-sdk,
structlog, rich, typer.
src/attune/
├── agents/ # Release agents, state persistence, recovery
├── workflows/ # AI-powered workflows (all SDK-native)
├── models/ # Auth strategy and LLM providers
├── meta_workflows/ # Intent detection, NL routing
├── orchestration/ # Dynamic teams, workflow composition
├── plugins/ # BasePlugin + register_mcp_tools() hook
├── telemetry/ # FeedbackLoop, UsageTracker
└── cli_router.py # NL command routing
attune_redis/ # Redis plugin — bundled in the attune-ai wheel
Cross-provider collaboration
Principles
Every principle below names its enforcer — the ratchet, gate, hook, or drift-guard test that makes it true without anyone remembering it. A principle marked aspirational has no mechanical enforcer yet: treat it as binding discipline, and treat adding its enforcer as pickable work.
- The receipt beats the promise. "Configured", "registered",
and "exited 0" are claims; evidence of the user-visible behavior
is the receipt. Delegated lanes declare their receipt type at
launch and the lead re-runs receipts centrally.
*Surfaces enforcer:
tests/unit/gates/test_surface_parity.pychecks producer coverage, registry integrity, executed package receipts, and explicit outstanding runtime obligations. Inventory success is not complete parity: pending obligations and experiments cannot satisfy route evidence requirements. Parity assertions cover only registry-named subjects; production routing and lifecycle receipts remain open until implemented. Other receipt discipline remains aspirational (ruled discipline —.claude/rules/attune/decision-routine.mddelegation receipts- this contract's Verification receipts section; no mechanical gate).*
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 Changed · +4 lines · +69 tokens per session f3ec08d82e30
- 1mo ago Changed · +26 lines · +335 tokens per session a885377d97c2
- 1mo ago First seen · 452 lines · 5,405 tokens per session scan A 749f76c7b8bf
attune-ai AGENTS.md is an instructions file published in the GitHub repository Smart-AI-Memory/attune-ai (10 stars, last pushed today), licensed Apache-2.0. It adds 5,809 tokens to every session, about $0.0232 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 2026-08-31.
Other instructions, from other repositories
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).
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.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
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.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deno copilot-instructions.md
Copilot instructions for denoland/deno, covering deno development guide for github copilot, network access, high level overview, key directories and key files to understand first.