Borrowing it
Nothing to install: this file belongs to remyxai/outrider. 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/remyxai/outrider/main/AGENTS.mdgit clone --depth 1 https://github.com/remyxai/outriderWrote 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/remyxai/outrider/agents-md)<a href="https://agentmods.dev/instructions/remyxai/outrider/agents-md"><img src="https://agentmods.dev/badge/instructions/remyxai/outrider/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/remyxai/outrider/agents-md"><img src="https://agentmods.dev/badge/instructions/remyxai/outrider/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 | $0.01717 | $0.01717 |
| Opus 5 | $0.00859 | $0.00859 |
| Sonnet 5 | $0.00343 | $0.00343 |
| Haiku 4.5 | $0.00172 | $0.00172 |
Grade A, and why
outrider 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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Outrider
Guidance for AI coding agents working on this repository. Read this before touching source.
What this project is
Outrider is a GitHub Action that turns arXiv papers into draft PRs on target repos. It:
- Queries the Remyx engine for a paper recommendation against a repo's
ResearchInterest. - Clones the target repo, drafts an implementation via Claude Code, runs pytest + self-review.
- Opens a draft PR (or Issue when preflight downgrades) attributed to
remyx-ai[bot]. - Optionally runs an inline refinement chain: fidelity audit → convention pass → test gate.
The Action is backend-agnostic through Claude Code's Anthropic-Messages-compatible endpoints — Anthropic (default), z.ai/GLM, Moonshot/Kimi via the provider action input.
Build & test
- Full test suite:
python3 -m pytest tests/ -q(~15s, ~1050 tests + 1 skipped) - Targeted:
python3 -m pytest tests/test_bot_token_default.py -x -q - Validate
action.yml:python3 -c "import yaml; yaml.safe_load(open('action.yml'))" - No
pip install -e .; the action installs its own deps inaction.yml's composite steps.
Run tests before every commit. New behavior needs pinning tests before the PR opens.
Architecture at a glance
src/run.py— main logic (~16K LOC, one file, intentionally). Selection, preflight, coding invocation, chain phases, cost telemetry, bot-token minting — all in here. Search fordefbefore adding a function; the piece you want probably exists.action.yml— composite-action step definitions. Inputs threaded intorun.pyviaINPUT_*env vars. Adding a new input means anaction.ymlentry + a reader inrun.py.tests/— every phase has its owntest_*.pyfile. Tests intercept subprocess calls, GitHub API calls, and Claude CLI calls with monkeypatch stubs.docs/— customer-facing docs.backends.mdis the canonical vendor table.customization.mdis the input-shape reference.
Backend routing (provider input)
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 · 88 lines · 1,717 tokens per session scan A 9115e5d51d1e
outrider AGENTS.md is an instructions file published in the GitHub repository remyxai/outrider (20 stars, last pushed today), licensed Apache-2.0. It adds 1,717 tokens to every session, about $0.0086 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.