Borrowing it
Nothing to install: this file belongs to erans/autoagent-action. 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/erans/autoagent-action/main/AGENTS.mdgit clone --depth 1 https://github.com/erans/autoagent-actionWrote 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/erans/autoagent-action/agents-md)<a href="https://agentmods.dev/instructions/erans/autoagent-action/agents-md"><img src="https://agentmods.dev/badge/instructions/erans/autoagent-action/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/erans/autoagent-action/agents-md"><img src="https://agentmods.dev/badge/instructions/erans/autoagent-action/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 | $0.01807 | $0.01807 |
| Opus 5.5 | $0.00723 | $0.00723 |
| Sonnet 5.5 | $0.00361 | $0.00361 |
| Haiku 4.5 | $0.00181 | $0.00181 |
Grade A, and why
autoagent-action 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 1mo 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AutoAgent Project Structure
AutoAgent is a composable GitHub Action that integrates with multiple AI agents (Cursor CLI, Claude Code, Gemini CLI, Codex CLI, Amp Code, and OpenCode) to run automated code analysis and prompts on repositories as part of Pull Request workflows.
Project Overview
AutoAgent provides a standardized way to run AI-driven code analysis in GitHub Actions, offering predefined security checks, code reviews, and refactoring suggestions, plus support for custom prompts. It automatically installs the required AI agent and posts structured results back to the PR as comments.
Directory Structure
Root Files
| File | Purpose |
|---|---|
action.yml |
GitHub Action definition with inputs, outputs, and execution steps |
README.md |
User documentation with usage examples and configuration options |
results.json |
Temporary file storing analysis results in JSON format |
test.sh |
Comprehensive test script that validates the entire implementation |
test-simple.sh |
Lightweight test script for syntax validation and basic functionality |
/docs/ - Documentation
| File | Purpose |
|---|---|
prd.md |
Product Requirements Document defining features, inputs, and behavior |
tech-prd.md |
Technical Implementation Guide with architecture and code structure details |
/rules/ - AI Agent Prompts
Contains predefined prompt templates that guide the AI agent's analysis:
| File | Purpose |
|---|---|
base.prompt |
Shared initialization context for all agents running in GitHub Actions |
code-review.prompt |
Comprehensive code review focusing on quality, architecture, performance, and maintainability |
owasp-check.prompt |
Security analysis based on OWASP Top 10 guidelines |
refactor-suggestions.prompt |
Code smell detection and refactoring opportunity identification |
comment.prompt |
Output formatting instructions for PR comments (concise, actionable, with compare links) |
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.
- 1mo ago First seen · 174 lines · 1,807 tokens per session scan A 0a642911c49c
autoagent-action AGENTS.md is an instructions file published in the GitHub repository erans/autoagent-action (17 stars, last pushed 1y ago), licensed MIT. It adds 1,807 tokens to every session, about $0.0072 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 2026-08-30.
Other instructions, from other repositories
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).
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.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
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.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
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.