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/agentscope-ai/agentteams/agents-mdgit clone --depth 1 https://github.com/agentscope-ai/AgentTeamsWrote 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/agentscope-ai/agentteams/agents-md)<a href="https://agentmods.dev/instructions/agentscope-ai/agentteams/agents-md"><img src="https://agentmods.dev/badge/instructions/agentscope-ai/agentteams/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 | $0.04263 | $0.04263 |
| Opus 5 | $0.02132 | $0.02132 |
| Sonnet 5 | $0.00853 | $0.00853 |
| Haiku 4.5 | $0.00426 | $0.00426 |
Grade A, and why
AgentTeams 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 4d 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 — 273 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AgentTeams Codebase Navigation Guide
This file helps AI Agents (and human developers) quickly understand the project structure and find relevant code.
What is AgentTeams
AgentTeams is an open-source Agent Teams system that uses IM (Matrix protocol) for multi-Agent collaboration with human-in-the-loop oversight. It consists of a Manager Agent (coordinator) and Worker Agents (task executors), connected via an AI Gateway (Higress), Matrix Homeserver (Tuwunel), and HTTP file storage (MinIO or cloud OSS). Production-style deployments use the Kubernetes operator and Helm chart; local installs use Docker Compose scripts under install/.
Project Structure
AgentTeams/
├── agentteams-controller/ # Kubernetes operator (Go): reconciles Worker, Manager, Team, Human CRDs
├── helm/ # Helm chart (K8s): Higress, Tuwunel, MinIO, controller, Manager CR, defaults
├── manager/ # Manager images: OpenClaw-based (Dockerfile) and CoPaw-based (Dockerfile.qwenpaw)
├── worker/ # OpenClaw Worker image (shared base pattern; runtime also selected at deploy time)
├── copaw/ # CoPaw Python package source (published as e.g. copaw-worker on PyPI)
├── hermes/ # Hermes Python package source (Hermes Matrix worker runtime)
├── openhuman/ # OpenHuman Worker image: Rust core + native Matrix (channel-matrix feature)
├── openclaw-base/ # Base image: Ubuntu + Node.js + bundled agent assets + mcporter
├── shared/lib/ # Shared shell libs copied into images (agentteams-env.sh, render-skills.sh, …)
├── install/ # Local install scripts (Docker Compose / embedded “all-in-one” stack)
├── scripts/ # Project-level utilities (e.g. replay-task.sh)
├── tests/ # Automated integration tests
├── docs/ # User-facing documentation
├── design/ # Internal design notes and API specs
├── changelog/ # Archived release notes from earlier releases
├── hack/ # Maintenance helpers (e.g. image mirror scripts)
├── migrate/ # Optional migration helpers
├── blog/ # Announcement / blog source
└── .github/workflows/ # CI: build images, tests, release automation
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.
- 4d ago First seen · 273 lines · 4,263 tokens per session scan A ceec080a70e1
AgentTeams AGENTS.md is an instructions file published in the GitHub repository agentscope-ai/AgentTeams (5,552 stars, last pushed 2d ago), licensed Apache-2.0. It adds 4,263 tokens to every session, about $0.0213 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 2026-08-30.
Other instructions, from other repositories
BitFun AGENTS.md
AGENTS.md instructions for GCWing/BitFun, covering agents.md, quick start, layered module index, common commands and setup and primary product loop.
librefang AGENTS.md
AGENTS.md instructions for librefang/librefang, covering stack, layout, build, architecture and kernelhandle trait.
autonomous-os AGENTS.md
AGENTS.md instructions for autonomous-ai/autonomous-os, covering agents.md, multi-ide rules, working style, parallel work / subagents and device access rules.
OneManCompany CLAUDE.md
Instructions for 1mancompany/OneManCompany, covering gstack and skill routing.
souls-directory CLAUDE.md
Instructions for thedaviddias/souls-directory, covering claude.md — project context for ai assistants, project overview, tech stack, critical rules and database is convex.
jentic-one GEMINI.md
Instructions for jentic/jentic-one: Otherwise, read AGENTS.md — this repo's canonical agent guidance.