Borrowing it
Nothing to install: this file belongs to mnzralee/claude-multi-agent-architecture. 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/mnzralee/claude-multi-agent-architecture/main/CLAUDE.mdgit clone --depth 1 https://github.com/mnzralee/claude-multi-agent-architectureWrote 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/mnzralee/claude-multi-agent-architecture/claude-md)<a href="https://agentmods.dev/instructions/mnzralee/claude-multi-agent-architecture/claude-md"><img src="https://agentmods.dev/badge/instructions/mnzralee/claude-multi-agent-architecture/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/mnzralee/claude-multi-agent-architecture/claude-md"><img src="https://agentmods.dev/badge/instructions/mnzralee/claude-multi-agent-architecture/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 | $0.01685 | $0.01685 |
| Opus 5 | $0.00843 | $0.00843 |
| Sonnet 5 | $0.00337 | $0.00337 |
| Haiku 4.5 | $0.00169 | $0.00169 |
Grade A, and why
claude-multi-agent-architecture CLAUDE.md scanned grade A with 1 finding 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 9d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- `curl`/`wget` and destructive git are denied by default; enable narrowly in `settings.local.json` when a task needs them. How it starts
The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
[PROJECT_NAME] - Claude Code Instructions
Multi-agent orchestration project. Cross-tool config in
AGENTS.md; full guides indocs/; enforcement rules in.claude/rules/.
Quick start (every session)
- Read today's work record:
docs/workrecords/work-record-YYYY-MM-DD.md(create it if missing). - Understand current state before changing anything. Verify names, paths, and configs from source; never assume them.
- For non-trivial work, follow Explore to Plan to Code to Commit (
/plan-feature). If you can describe the whole diff in one sentence, skip the plan and just do it, then verify.
Common commands
# [CUSTOMIZE: your project's real commands]
npm run dev # start dev server
npm run build # build
npm test # run tests
npm run lint # lint
When rules conflict
Priority: security > correctness > performance > readability > style. If a rule file and this file disagree, this file wins. If two agents propose incompatible changes, the orchestrator decides; do not silently pick one.
Rule enforcement tiers (the rules live in .claude/rules/):
| Tier | Meaning | Examples |
|---|---|---|
| P0 Always enforce | Block on violation | No secrets in code; no swallowed errors; auth on non-public endpoints; no any in production |
| P1 Strongly prefer | Flag in review | Clean-architecture boundaries; coverage thresholds; explicit error handling |
| P2 Nice to have | Suggest, do not block | Naming, import order, doc completeness |
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.
- 9d ago First seen · 107 lines · 1,685 tokens per session scan A a0eabe98b78d
claude-multi-agent-architecture CLAUDE.md is an instructions file published in the GitHub repository mnzralee/claude-multi-agent-architecture (6 stars, last pushed 1mo ago), licensed MIT. It adds 1,685 tokens to every session, about $0.0084 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). 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.
deepseek-harness AGENTS.md
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.