Swarms is a Python framework for coordinating multiple autonomous language-model agents into workflows such as sequential, concurrent, or hierarchical systems. It is used to build multi-step applications in which agents combine language models, tools, and memory. The catalogue entries provide agent-oriented skills, instructions, and an agent for working with Swarms.
Borrowing it
Nothing to install: this file belongs to kyegomez/swarms. 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/kyegomez/swarms/master/AGENTS.mdgit clone --depth 1 https://github.com/kyegomez/swarmsWrote 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/kyegomez/swarms/agents-md)<a href="https://agentmods.dev/instructions/kyegomez/swarms/agents-md"><img src="https://agentmods.dev/badge/instructions/kyegomez/swarms/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/kyegomez/swarms/agents-md"><img src="https://agentmods.dev/badge/instructions/kyegomez/swarms/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 | $0.00643 | $0.00643 |
| Opus 5.5 | $0.00257 | $0.00257 |
| Sonnet 5.5 | $0.00129 | $0.00129 |
| Haiku 4.5 | $0.00064 | $0.00064 |
Grade A, and why
swarms 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 8d 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 — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Guidance for AI coding agents (Codex, Cursor, Copilot, Jules, Claude Code and others) working with Swarms, a multi-agent orchestration framework for Python.
Quickstart
pip install -U swarms
export OPENAI_API_KEY="sk-..." # or any provider key
from swarms import Agent
agent = Agent(agent_name="Analyst", model_name="gpt-5.4", max_loops=1)
print(agent.run("Summarise the current state of LLM research."))
Where to look
CLAUDE.md: the full guide.Agentparameters, every multi-agent structure, tools, streaming, memory, MCP, and how to choose between them. Read it before writing Swarms code.SKILL.md: a condensed version packaged as an agent skill.examples/: hundreds of runnable examples. One is probably close to what you need.- Docs MCP server:
https://docs.swarms.world/mcp, no key. Search the current docs instead of relying on training data; names changed across v12 to v16. - Marketplace MCP server:
https://swarms.world/mcp. Listing tools needs no key; calling them needs a Swarms API key asAuthorization: Bearer <key>. - Plain-text docs: llms.txt and llms-full.txt.
Rules
- Import from the top level:
from swarms import Agent, notfrom swarms.structs.agent import Agent. - Give every agent a unique
agent_name; memory and routing key on it. - Prefer an explicit
max_loops=N. Use"auto"only for open-ended work. - Don't set
streaming_on=Trueandstreaming_callbackon the same agent.
Contributing to this repository
- Commit, PR and issue titles use WARP:
[TYPE][Function/FileName][Short description]. - Disclose AI authorship: a co-author trailer on commits and a "Generated with" line naming the agent and model on PRs and issues.
- Format with
black --line-length 70and lint withruff check .. - Removing unused code (a method, parameter, attribute or line) needs no new unit test. Delete the tests that only exercised it and run the module's existing tests.
- Not every change needs a unit test. When you add one, keep it small and fast: one table-driven test per behaviour, stubbed model and network, no near-copies.
- User-visible changes need a matching PR in swarms-framework-docs.
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.
- 8d ago Changed · +2 lines · +73 tokens per session 7d402f7bb763
- 10d ago First seen · 43 lines · 570 tokens per session scan A 307d5cd11d4b
swarms AGENTS.md is an instructions file published in the GitHub repository kyegomez/swarms (7,353 stars, last pushed yesterday), licensed Apache-2.0. It adds 643 tokens to every session, about $0.0026 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 2026-10-27.
swarms AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| swarms AGENTS.mdkyegomez/swarms | Instructions file | 7.4k | yesterday | Apache-2.0 | A | 643 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 5,516 | GitHub Copilot |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | today | MIT | A | 4,680 | Codex, OpenCode |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |