Borrowing it
Nothing to install: this file belongs to AutomatosAI/automatos-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/AutomatosAI/automatos-ai/main/CLAUDE.mdgit clone --depth 1 https://github.com/AutomatosAI/automatos-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/automatosai/automatos-ai/claude-md)<a href="https://agentmods.dev/instructions/automatosai/automatos-ai/claude-md"><img src="https://agentmods.dev/badge/instructions/automatosai/automatos-ai/claude-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/automatosai/automatos-ai/claude-md"><img src="https://agentmods.dev/badge/instructions/automatosai/automatos-ai/claude-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 | $0.01779 | $0.01779 |
| Opus 5.5 | $0.00712 | $0.00712 |
| Sonnet 5.5 | $0.00356 | $0.00356 |
| Haiku 4.5 | $0.00178 | $0.00178 |
Grade A, and why
automatos-ai CLAUDE.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 — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md — Automatos AI Platform
@AGENTS.md
The rules every contributor and coding agent follows are in AGENTS.md, imported above. This file adds the maintainer's Claude workflow: memory, the graph, PRD framing and scope. It complements the user's global
~/.claude/CLAUDE.md.
1. Where this project is
Automatos is at PRD 136+, not greenfield. The platform has 109 SQLAlchemy tables, 103 API routers, 599 frontend TS files, and a Knowledge Graph mapping every code path. Most "new" work isn't new — it's rehousing, refactoring, consolidating, or extending what already exists.
Treat this codebase like a mature product, not a startup MVP.
2. Default mindset: REUSE over BUILD
Before writing any code for a PRD, work through this order:
- Search the graph first.
graphify-out/graph.json,GRAPH_REPORT.md,db.json— these exist for a reason. Use them. - Search the codebase. Component, hook, table, endpoint — does it already exist?
- Read the relevant memory files at
~/.claude/projects/-Users-gkavanagh-Development-Automatos-AI-Platform-automatos-ai/memory/MEMORY.md— many concepts (Playbooks, Missions, Tasks, tools, plumbing) are documented there. - Then decide: reuse, extend, refactor, or build new.
If you're about to write a new component/hook/table/endpoint, the burden is on you to justify why the existing one isn't enough.
3. PRD framing — what type is this?
Before estimating or implementing, classify the PRD:
| Type | Signal | Default action |
|---|---|---|
| Rehouse / IA change | "Move X from Y to Z", "rename", "redesign page" | Components, hooks, APIs already exist. Move/relabel, don't rebuild. |
| Refactor / Consolidation | "Unify X and Y", "deprecate", "single source of truth" | Pick the canonical path, migrate the others, delete the losers. |
| Extension | "Add X to existing Y" | New code is the increment, not the system. |
| Net-new feature | No precedent in the platform | Justify why it doesn't fit an existing pattern. Build small, prove the value, then expand. |
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 · -16 lines · -275 tokens per session c8461283588f
- 1mo ago First seen · 163 lines · 2,054 tokens per session scan A 6be240afbaf8
automatos-ai CLAUDE.md is an instructions file published in the GitHub repository AutomatosAI/automatos-ai (74 stars, last pushed today), licensed Apache-2.0. It adds 1,779 tokens to every session, about $0.0071 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 2026-08-30.
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.
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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.
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AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.