AGENTS.md Management

Tools to maintain and improve AGENTS.md files — audit quality, capture session learnings, and keep project memory current.

What It Does

Two complementary features for different purposes:

	agent-md-improver (skill)	/revise-agent-md (command)
Purpose	Keep AGENTS.md aligned with codebase	Capture session learnings
Triggered by	Codebase changes	End of session
Use when	Periodic maintenance	Session revealed missing context

Usage

Skill: agent-md-improver

Audits AGENTS.md files against current codebase state:

/audit my AGENTS.md files
/check if my AGENTS.md is up to date

The skill scans all AGENTS.md files, evaluates them against quality criteria, outputs a detailed quality report, and (with your approval) applies targeted improvements.

Command: /revise-agent-md

Captures learnings from the current session:

/revise-agent-md

Reviews the current session for missing context, patterns, commands, and gotchas that should be documented in AGENTS.md. Shows proposed changes with diffs and applies them with your approval.

Installation

Install from npm:

pi install npm:@lynskylate/agent-md-management

Install from GitHub:

pi install git:github.com/Lynskylate/agent-md-management

Or install locally:

pi install /path/to/agent-md-management

What Makes a Great AGENTS.md

• Concise and human-readable — Dense is better than verbose
• Actionable commands — Everything copy-paste ready
• Project-specific patterns — Not generic advice
• Non-obvious gotchas — Things an AI agent can't easily infer
• Up to date — Reflects current codebase state

Inspiration

Inspired by claude-md-management from Anthropic's official Claude Code plugins.

License

Apache-2.0