OpenSwarm is an open-source multi-agent system in which specialized agents coordinate to produce deliverables such as presentations, research reports, data visualizations, documents, images, and videos. It is intended for people who want to request complex creative or analytical work from a terminal, with connections to external services. Its catalogue entries define agents, commands, rules, and instructions for those workflows.
Borrowing it
Nothing to install: this file belongs to VRSEN/OpenSwarm. 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/VRSEN/OpenSwarm/main/CLAUDE.mdgit clone --depth 1 https://github.com/VRSEN/OpenSwarmWrote 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/vrsen/openswarm/claude-md)<a href="https://agentmods.dev/instructions/vrsen/openswarm/claude-md"><img src="https://agentmods.dev/badge/instructions/vrsen/openswarm/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/vrsen/openswarm/claude-md"><img src="https://agentmods.dev/badge/instructions/vrsen/openswarm/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 | $0.01865 | $0.01865 |
| Opus 5.5 | $0.00746 | $0.00746 |
| Sonnet 5.5 | $0.00373 | $0.00373 |
| Haiku 4.5 | $0.00186 | $0.00186 |
Grade D, and why
OpenSwarm CLAUDE.md scanned grade D with 2 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.
Asks the agent to reveal its instructionsmediumSystem prompt leakage
Directions to print, repeat or translate the system prompt extract configuration the operator did not intend to expose.
- OPENAI_API_KEY (required) - Show instructions how to get it Harvests environment variableshighData exfiltration
Enumerating or grepping the environment for keys collects credentials unrelated to what the mod says it does.
6. **Collect API keys BEFORE development** (with instructions from api-researcher): Copies of this mod
1 near-identical copy found in the catalogue:
- mcp-skill-creator-agency CLAUDE.md — 92% identical, 24 lines differ
How it starts
The opening of the file, as written. The whole thing — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agency Builder
You are a specialized agent that coordinates specialized sub-agents to build production-ready Agency Swarm v1.0.0 agencies.
Before proceeding with agent creation, please read the following instructions carefully:
.cursor/rules/agency-swarm-workflow.mdc- your primary guide for creating agents and agencies
The following files can be read on demand, depending on the task at hand:
.cursor/commands/add-mcp.md- how to add MCP servers to an agent.cursor/commands/mcp-code-exec.md- how to convert an MCP server into the Code Execution Pattern (progressive tool disclosure, 98% token reduction).cursor/commands/write-instructions.md- how to write effective instructions for AI agents.cursor/commands/create-prd.md- how to create a PRD for an agent (use for complex multi agent systems)
Background
Agency Swarm is an open-source framework designed for orchestrating and managing multiple AI agents, built upon the OpenAI Assistants API. Its primary purpose is to facilitate the creation of "AI agencies" or "swarms" where multiple AI agents with distinct roles and capabilities can collaborate to automate complex workflows and tasks.
A Note on Communication Flow Patterns
In Agency Swarm, communication flows are uniform, meaning you can define them in any way you want. Below are some examples:
Orchestrator-Workers (Most Common)
agency = Agency(
ceo, # Entry point for user communication
communication_flows=[
(ceo, worker1),
(ceo, worker2),
(ceo, worker3),
],
shared_instructions="agency_manifesto.md",
)
Sequential Pipeline (handoffs)
from agency_swarm.tools.send_message import SendMessageHandoff
# Each agent needs SendMessageHandoff as their send_message_tool_class
agent1 = Agent(..., send_message_tool_class=SendMessageHandoff)
agent2 = Agent(..., send_message_tool_class=SendMessageHandoff)
agency = Agency(
agent1,
communication_flows=[
(agent1, agent2),
(agent2, agent3),
],
shared_instructions="agency_manifesto.md",
)
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 · 193 lines · 1,865 tokens per session scan D a1ee5ac845d8
OpenSwarm CLAUDE.md is an instructions file published in the GitHub repository VRSEN/OpenSwarm (2,873 stars, last pushed 3mo ago), licensed MIT. It adds 1,865 tokens to every session, about $0.0075 per session on Opus 5.5. A static security scan graded it D with 2 findings (asks the agent to reveal its instructions, harvests environment variables). 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).
vscode model-prompts.instructions.md
Model-specific prompt authoring and registry guidelines.