agents-md-guide

Guide for using and supporting the AGENTS.md standard in VS Code. Use this when asked about AGENTS.md, custom instructions, or repo-level AI agent configuration.

$ 安裝

git clone https://github.com/raphaelmansuy/machine-learning-feature-selection /tmp/machine-learning-feature-selection && cp -r /tmp/machine-learning-feature-selection/.github/skills/agents-md-guide ~/.claude/skills/machine-learning-feature-selection

// tip: Run this command in your terminal to install the skill

SKILL.md

View on GitHub →

name: agents-md-guide description: Guide for using and supporting the AGENTS.md standard in VS Code. Use this when asked about AGENTS.md, custom instructions, or repo-level AI agent configuration.

AGENTS.md Guide for VS Code

This skill provides guidance on implementing and using the AGENTS.md standard to provide custom instructions for AI coding agents in VS Code.

Why AGENTS.md?

Standardization: Reduces fragmentation from proprietary files like .cursorrules.
Interoperability: Works across different AI tools (GitHub Copilot, Cursor, etc.).
Efficiency: Saves time by providing structured context (build steps, coding conventions).
Consistency: Ensures AI agents follow project-specific protocols.
Open Standard: Governed by the Agentic AI Foundation (Linux Foundation).

Mental Model

AGENTS.md acts as a centralized instruction manual for AI coding agents at the repo root.

Flow: Repo clone → agent scans for AGENTS.md → parses sections → applies rules during tasks → outputs aligned code.

VS Code Configuration

To enable AGENTS.md support in VS Code:

Enable Setting: Set chat.useAgentsMdFile to true.
Nested Files (Experimental): Set chat.useNestedAgentsMdFiles to true for subfolder instructions.

How to Implement AGENTS.md

Location: Place AGENTS.md at the root of your repository.
Structure: Use clear sections:
- ## Environment: Setup and build instructions.
- ## Coding Style: Linting, formatting, and architectural rules.
- ## Testing: How to run and write tests.
Keep it Concise: Avoid overly verbose rules.

Real-World Scenarios

Open-source Maintenance: AI agents auto-generate PRs following style guides.
Enterprise Code Reviews: Teams use repo-level rules during Copilot-assisted edits.
Indie Dev Prototyping: Automate build and test cycles with tools like Cursor or Codex.

Survival Kit

Day 0: Clone a repo with AGENTS.md; ensure chat.useAgentsMdFile is enabled in VS Code.
Week 1: Create a basic AGENTS.md in a test repo and iterate on sections.
Week 2: Add nested files if needed using experimental settings.

Security & Risks

No Secrets: Never include API keys or credentials.
Goal Hijacking: Be aware that instruction files can steer agent behavior. Review instructions before running autonomous tasks in untrusted repos.