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/AGENTS.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/agents-md)<a href="https://agentmods.dev/instructions/vrsen/openswarm/agents-md"><img src="https://agentmods.dev/badge/instructions/vrsen/openswarm/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/vrsen/openswarm/agents-md"><img src="https://agentmods.dev/badge/instructions/vrsen/openswarm/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 | $0.01053 | $0.01053 |
| Opus 5.5 | $0.00421 | $0.00421 |
| Sonnet 5.5 | $0.00211 | $0.00211 |
| Haiku 4.5 | $0.00105 | $0.00105 |
Grade A, and why
OpenSwarm 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenSwarm — Customization Guide
This file gives coding agents (Cursor, Claude Code, Codex, etc.) everything they need to understand and customize this swarm. Read it before making any changes.
What is OpenSwarm?
OpenSwarm is a multi-agent AI team you can fork and reshape into any kind of swarm you need — SEO, sales, research, finance, customer support, or anything else. Each agent is a specialist. They collaborate through a shared orchestrator.
Folder Structure
swarm.py ← main config: imports all agents, defines how they connect
shared_instructions.md ← context shared across every agent
run.py ← CLI entry point (terminal demo)
server.py ← API entry point (FastAPI server)
orchestrator/
orchestrator.py ← agent definition
instructions.md ← system prompt
data_analyst_agent/
data_analyst_agent.py
instructions.md
tools/ ← custom tools for this agent
docs_agent/
docs_agent.py
instructions.md
tools/
slides_agent/
slides_agent.py
instructions.md
tools/
image_generation_agent/
image_generation_agent.py
instructions.md
tools/
video_generation_agent/
video_generation_agent.py
instructions.md
tools/
deep_research/
deep_research.py
instructions.md
tools/
virtual_assistant/
virtual_assistant.py
instructions.md
tools/
shared_tools/ ← tools available to all agents (Composio integrations, etc.)
How Agents Connect (swarm.py)
swarm.py is the only file you need to edit when adding, removing, or rewiring agents. It:
- Imports a
create_*factory function from each agent folder - Instantiates all agents
- Defines communication flows — who can talk to whom
The default pattern is orchestrator-to-all: the orchestrator can send messages to every specialist, and all agents can hand off to each other.
How to Customize
To build your own swarm from this repo:
- Fork and rename the repo (e.g.,
seo-swarm) - Decide which agents to keep, rename, or replace
- Rename the folder and its files to match the new agent's purpose
- Update
instructions.mdwith the new system prompt - Update
swarm.pyto import and register the renamed agent
- Add or remove tools inside each agent's
tools/folder - Update
shared_instructions.mdwith any context all agents should share - Run with
python run.py
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 · 131 lines · 1,053 tokens per session scan A 71a3168c70d6
OpenSwarm AGENTS.md is an instructions file published in the GitHub repository VRSEN/OpenSwarm (2,873 stars, last pushed 3mo ago), licensed MIT. It adds 1,053 tokens to every session, about $0.0042 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).
vscode model-prompts.instructions.md
Model-specific prompt authoring and registry guidelines.