Borrowing it
Nothing to install: this file belongs to xg-gh-25/SwarmAI. 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/xg-gh-25/SwarmAI/main/AGENTS.mdgit clone --depth 1 https://github.com/xg-gh-25/SwarmAIWrote 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/xg-gh-25/swarmai/agents-md)<a href="https://agentmods.dev/instructions/xg-gh-25/swarmai/agents-md"><img src="https://agentmods.dev/badge/instructions/xg-gh-25/swarmai/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/xg-gh-25/swarmai/agents-md"><img src="https://agentmods.dev/badge/instructions/xg-gh-25/swarmai/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 | $0.05366 | $0.05366 |
| Opus 5 | $0.02683 | $0.02683 |
| Sonnet 5 | $0.01073 | $0.01073 |
| Haiku 4.5 | $0.00537 | $0.00537 |
Grade A, and why
SwarmAI 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 9d 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 — 368 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Guidance for AI coding assistants (Claude Code, Kiro, Cursor, Codex, and others) working in this repository.
Auto-refresh: the <!-- CAPABILITIES --> block below is regenerated by
backend/scripts/refresh_ai_docs.py; everything else is hand-authored. Edit prose
freely — just keep the marked block and the section headings intact.
What SwarmAI Is (read this first — it changes how you should judge the code)
SwarmAI is a self-evolving Agent OS, not a chatbot and not a Claude wrapper. The distinction is load-bearing for anyone editing this repo:
- Cognition is separated from knowledge. The OS (how the system judges — its principles, rules, and gates) is deliberately kept apart from the disk (what it knows — memory rows, domain docs). One edited line in a governed context file shifts judgment more than a thousand knowledge entries. When you touch this codebase, ask which layer you're in: a behavior change is an OS change; a fact change is a disk change. They have different review bars.
- The model proposes, the OS disposes. Model output is never trusted on its own.
A layer of gates, a staged pipeline, and a validator sit above it and hold authority.
This is why so much of
backend/core/looks like "guardrails around an LLM" — that is the product. - Value compounds across sessions. Sessions are discontinuous; intelligence shouldn't be. Post-session hooks fire between runs (distillation, evolution, context-health, cultivation), so the next session starts warmer than the last. Code that runs after a session ends is not an afterthought here — it's the mechanism.
- A recurring error class becomes a structural gate. When the same mistake shows up
3+ times, the fix is not another prose rule — it's a gate in
security_hooks.pywhere the wrong move physically cannot happen. If you're tempted to "add a warning comment," consider whether a gate is the real fix. - Every project is a domain brain (a DDD). A project is not a folder of files — it's
a brain with one universal six-section structure (Identity · Knowledge · Gates ·
Capabilities · Delivery · Refresher), identical for every domain, governing
0..Nassets (a code repo, a data source, a corpus — or nothing). SeeProjects/*/.
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.
- 9d ago First seen · 368 lines · 5,366 tokens per session scan E 39c72625d39a
SwarmAI AGENTS.md is an instructions file published in the GitHub repository xg-gh-25/SwarmAI (44 stars, last pushed 2d ago), licensed MIT. It adds 5,366 tokens to every session, about $0.0268 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
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.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
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).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
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.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.