Borrowing it
Nothing to install: this file belongs to raysonmeng/agent-bridge. 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/raysonmeng/agent-bridge/master/AGENTS.mdgit clone --depth 1 https://github.com/raysonmeng/agent-bridgeWrote 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/raysonmeng/agent-bridge/agents-md)<a href="https://agentmods.dev/instructions/raysonmeng/agent-bridge/agents-md"><img src="https://agentmods.dev/badge/instructions/raysonmeng/agent-bridge/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/raysonmeng/agent-bridge/agents-md"><img src="https://agentmods.dev/badge/instructions/raysonmeng/agent-bridge/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 | $0.00726 | $0.00726 |
| Opus 5.5 | $0.00290 | $0.00290 |
| Sonnet 5.5 | $0.00145 | $0.00145 |
| Haiku 4.5 | $0.00073 | $0.00073 |
Grade A, and why
agent-bridge 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AgentBridge — Multi-Agent Collaboration
You are working in a multi-agent environment powered by AgentBridge.
Another AI agent (Claude, by Anthropic) is available in a parallel session on this machine.
Communication happens via AgentBridge MCP tools — Claude has reply and get_messages tools.
When to collaborate vs. work solo
- Collaborate when the task benefits from a second perspective, parallel execution, or capabilities the other agent has.
- Work solo for simple, self-contained tasks where the coordination overhead isn't worth it.
- When in doubt, propose a task split to Claude rather than doing everything yourself.
Capability comparison
| Capability | Codex (you) | Claude |
|---|---|---|
| Sandboxed code execution | Yes | No |
| Reproduce & verify bugs | Strong | Limited |
| Architecture & planning | Moderate | Strong |
| Code review & analysis | Strong | Strong |
| Web search & docs | Limited | Yes |
| File editing & refactoring | Yes (via sandbox) | Yes (via tools) |
How to start collaborating
- When you receive a complex task, proactively propose a division of labor.
- State what you'll handle and what you'd like Claude to take on.
- Ask for Claude's agreement or counter-proposal before proceeding.
- After task completion, cross-review each other's work.
MCP Tools: code-review-graph
IMPORTANT: This project has a knowledge graph. ALWAYS use the code-review-graph MCP tools BEFORE using Grep/Glob/Read to explore the codebase. The graph is faster, cheaper (fewer tokens), and gives you structural context (callers, dependents, test coverage) that file scanning cannot.
When to use graph tools FIRST
- Exploring code:
semantic_search_nodesorquery_graphinstead of Grep - Understanding impact:
get_impact_radiusinstead of manually tracing imports - Code review:
detect_changes+get_review_contextinstead of reading entire files - Finding relationships:
query_graphwith callers_of/callees_of/imports_of/tests_for - Architecture questions:
get_architecture_overview+list_communities
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 First seen · 68 lines · 726 tokens per session scan A c9d7be95b287
agent-bridge AGENTS.md is an instructions file published in the GitHub repository raysonmeng/agent-bridge (415 stars, last pushed today), licensed MIT. It adds 726 tokens to every session, about $0.0029 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.
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.