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 instructions/chappygo-os/atomic-spec/agents-mdgit clone --depth 1 https://github.com/Chappygo-OS/Atomic-SpecWrote 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/chappygo-os/atomic-spec/agents-md)<a href="https://agentmods.dev/instructions/chappygo-os/atomic-spec/agents-md"><img src="https://agentmods.dev/badge/instructions/chappygo-os/atomic-spec/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 | $0.05287 | $0.05287 |
| Opus 5 | $0.02644 | $0.02644 |
| Sonnet 5 | $0.01057 | $0.01057 |
| Haiku 4.5 | $0.00529 | $0.00529 |
Grade A, and why
Atomic-Spec 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 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.
How it starts
The opening of the file, as written. The whole thing — 523 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Adding a New AI Agent to Atomic Spec
About Atomic Spec and the atomicspec CLI
Atomic Spec is a governance framework for AI-driven development — a customized fork of GitHub Spec Kit that enforces the Atomic Traceability Model (gated, atomic, context-pinned phases). See atomic-traceability-model.md for the governance model.
The atomicspec CLI (PyPI package: atomic-spec) bootstraps projects with the framework. It sets up the necessary directory structures, templates, and AI-agent integrations to support the four-phase Specify → Plan → Tasks → Implement workflow.
The framework supports 17+ AI coding assistants across two tiers:
- Supported tier (wired end-to-end, exercised on every release):
claude,gemini,copilot,cursor-agent,windsurf - Experimental tier (template-enforced governance, best-effort triage):
qwen,opencode,codex,kilocode,auggie,codebuddy,qoder,roo,q,amp,shai,bob
Agent matching for subagents is dynamic: keyword overlap between feature descriptions and YAML frontmatter description fields — no hard-coded agent lists in command templates.
This guide explains how to add a new agent to the supported or experimental tier.
General practices
- Any changes to
src/specify_cli/__init__.pyrequire a version rev inpyproject.tomland an entry inCHANGELOG.md. - Agent metadata (
AGENT_CONFIGandATOMIC_SPEC_COMMANDS) lives insrc/specify_cli/_config.py— a stdlib-only module that the release workflow imports viaimportlib.utilwithout installing CLI dependencies.
Adding New Agent Support
This section explains how to add support for new AI agents/assistants to the Specify CLI. Use this guide as a reference when integrating new AI tools into the Spec-Driven Development workflow.
Overview
Specify supports multiple AI agents by generating agent-specific command files and directory structures when initializing projects. Each agent has its own conventions for:
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 · 523 lines · 5,287 tokens per session scan A 026da56c4dd1
Atomic-Spec AGENTS.md is an instructions file published in the GitHub repository Chappygo-OS/Atomic-Spec (10 stars, last pushed 10d ago), licensed MIT. It adds 5,287 tokens to every session, about $0.0264 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
prp-manager CLAUDE.md
Instructions for willywg/prp-manager, covering claude.md, project overview, repository structure, key concepts and three workflows.
superpowers-zh CLAUDE.md
Instructions for jnMetaCode/superpowers-zh, covering superpowers — 贡献者指南, 如果你是 ai agent, pull request 要求, 我们不会接受的内容 and 第三方依赖.
spec-kit-zh AGENTS.md
Instructions for loulanyue/spec-kit-zh, covering agents.md, about spec kit and specify, general practices, adding new agent support and current supported agents.
Meta_Kim CLAUDE.md
Instructions for KimYx0207/Meta_Kim, covering metakim for claude code, fast read, what this repository is, claude code's role and canonical vs runtime files.
memorix GEMINI.md
Instructions for AVIDS2/memorix, covering memorix - cross-agent memory rules, session start - bind project, then load context, during session - capture important context, architecture & decisions and bug fixes & problem solving.
Ctxo CLAUDE.md
Instructions for alperhankendi/Ctxo, covering claude.md — ctxo, project overview, quick reference, dev (pnpm workspace) and usage (consumer).