Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/awslabs/autohelix/agents-mdgit clone --depth 1 https://github.com/awslabs/AutoHelixWrote 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/awslabs/autohelix/agents-md)<a href="https://agentmods.dev/instructions/awslabs/autohelix/agents-md"><img src="https://agentmods.dev/badge/instructions/awslabs/autohelix/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 | $0.00286 | $0.00286 |
| Opus 5 | $0.00143 | $0.00143 |
| Sonnet 5 | $0.00057 | $0.00057 |
| Haiku 4.5 | $0.00029 | $0.00029 |
Grade A, and why
AutoHelix 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 4d 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
Guidance for AI coding agents working on the AutoHelix codebase. This mirrors
the conventions in CLAUDE.md — read that for full detail.
Quick orientation
- AutoHelix runs AI agents in an iterative optimization loop. Each iteration is
isolated in a git worktree, validated against constraints, and only merged when
it passes. Start in
src/autohelix/harness.py. - See
README.mdfor user-facing docs and the config reference.
Working rules
- Setup: activate the venv first (
source .venv/bin/activate). The package is an editable install — edits undersrc/autohelix/are live, no reinstall needed. - Test before you finish:
pytest(fast suite). Usepytest -m slowonly when a real agent is needed. - Do not commit optimized example code —
examples/must keep the slow baseline so users can see the optimization potential. - Don't break backward compatibility in config parsing: new config keys should be
optional and gated, so existing
autohelix.yamlfiles keep working.
For architecture notes, gotchas, and project layout, see CLAUDE.md.
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.
- 4d ago First seen · 25 lines · 286 tokens per session scan A f0175d2d4797
AutoHelix AGENTS.md is an instructions file published in the GitHub repository awslabs/AutoHelix (18 stars, last pushed 27d ago), licensed Apache-2.0. It adds 286 tokens to every session, about $0.0014 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
html-anything AGENTS.md
AGENTS.md instructions for nexu-io/html-anything, covering this is not the next.js you know, workspace shape and commands.
codex-autoresearch AGENTS.md
Instructions for TheGreenCedar/codex-autoresearch, covering agents.md, purpose and scope, canonical sources, stable product boundaries and source and package boundaries.
framework AGENTS.md
AGENTS.md instructions for ai-driven-dev/framework, covering agents.md, behavior, communication, action and memory management.
platform CLAUDE.md
Claude Code instructions for ambient-code/platform, covering ambient code platform, structure, key files, session flow and commands.
autogen copilot-instructions.md
Copilot instructions for microsoft/autogen, covering autogen multi-agent ai framework, working effectively, prerequisites and environment setup, python development workflow and quick validation (under 1 second each).
toh-framework CLAUDE.md
Claude Code instructions for wasintoh/toh-framework, covering claude.md — toh framework (repo development guide), what this is, everyday commands, verification protocol and single source, transformed per ide.