Borrowing it
Nothing to install: this file belongs to PrimeIntellect-ai/nano-rlm. 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/PrimeIntellect-ai/nano-rlm/main/AGENTS.mdgit clone --depth 1 https://github.com/PrimeIntellect-ai/nano-rlmWrote 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/primeintellect-ai/nano-rlm/agents-md)<a href="https://agentmods.dev/instructions/primeintellect-ai/nano-rlm/agents-md"><img src="https://agentmods.dev/badge/instructions/primeintellect-ai/nano-rlm/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 5.1 | $0.00416 | $0.00416 |
| Opus 5 | $0.00208 | $0.00208 |
| Sonnet 5 | $0.00083 | $0.00083 |
| Haiku 4.5 | $0.00042 | $0.00042 |
Grade A, and why
nano-rlm 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 7d 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.
What it actually says
AGENTS.md
Writing code
- Minimal try/except: let errors propagate — silent failures hide bugs. Only catch for intentional fault tolerance (retries, robustness).
- Targeted comments: don't explain your work process or reference old code. Use comments sparingly to clarify ambiguous logic or non-obvious constraints.
- No "this replaced that" comments: never write comments or docstrings that reference code that used to exist. That context belongs in the PR, not in the file. Describe what the code does now, not what it isn't anymore.
Running code
- Always use uv: run code with
uv run, never rawpython. - Adding dependencies: add to
pyproject.tomland runuv sync(oruv sync --group devfor dev-only) to install and lock.
Testing
- Run the suite with
uv run pytest tests/. - Write tests as plain functions; don't use class-based tests.
- Conservative test additions: don't add new tests unless the user asks or it's clearly necessary. Editing existing tests is fine.
- Test what matters: only test code with clear, isolated logic. If you need to patch everything to make it testable, it's probably not worth testing.
Git
- Branch prefixes: use
feat/,fix/,chore/,docs/,tests/.
GitHub
- Draft PRs: always create PRs as drafts (
gh pr create --draft) to avoid triggering CI unnecessarily. - PR titles: start the title with a conventional-commit prefix matching the branch prefix (
feat:,fix:,chore:,docs:,tests:), e.g. adocs/...branch gets adocs: ...title. - Pull requests: do not include a "test plan" section unless you actually ran tests or the user explicitly asked for one.
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.
- 7d ago First seen · 30 lines · 416 tokens per session scan A 99e8963c0762
nano-rlm AGENTS.md is an instructions file published in the GitHub repository PrimeIntellect-ai/nano-rlm (53 stars, last pushed yesterday), licensed MIT. It adds 416 tokens to every session, about $0.0021 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.
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.