Verified:GitHub

agentic-engine-optimization

Audit project documentation and implement agent-friendly entry points like llms.txt and AGENTS.md.

1|Updated Jan 29, 2026

Search Tags:#documentation #llms.txt #AGENTS.md #coding agents #agent readiness #repo discoverability #capability signaling

Ready to run

npx skills add https://github.com/tho/skills --skill agentic-engine-optimization

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: agentic-engine-optimization
Source: https://github.com/tho/skills/tree/main/skills/agentic-engine-optimization
Command: npx skills add https://github.com/tho/skills --skill agentic-engine-optimization

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill helps you restructure project documentation so AI coding agents can quickly find, understand, and use your codebase with minimal friction.

Core Features & Use Cases

Agent-friendly documentation layout: Ensures key facts are accessible from plain-text entry points without relying on rendered pages or interactive navigation.
Capability signaling for faster decisions: Promotes outcomes, examples, and constraints so agents know what the project can do before deep-diving.
Systematic audit and targeted improvements: Uses an audit checklist to identify gaps and applies focused changes (often adding an index like llms.txt and agent entry points like AGENTS.md).

Quick Start

Use the agentic-engine-optimization skill to audit your repository for agent readiness and restructure documentation so agents can discover and use it efficiently.

Frequently Asked Questions about agentic-engine-optimization

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

What is agent readiness for a repository?▼

Agent readiness means restructuring project entry points and documentation so AI coding agents can discover, evaluate, and use the codebase with minimal friction through plain-text navigation.

How do I make my repository discoverable by AI coding agents?▼

Audit your repository against a checklist, then implement changes file-by-file by adding structured documentation indexes like llms.txt and agent entry points like AGENTS.md.

Do AI agents need llms.txt and AGENTS.md to navigate a codebase?▼

These files provide plain-text entry points that help agents find key facts and capabilities without rendered pages, significantly reducing friction during codebase discovery and evaluation.

What's the best way to format documentation for finite context coding agents?▼

Format documentation to support finite context by promoting outcomes, examples, and constraints upfront, and sizing instructions so agents know what the project can do before deep-diving.

Can I use agent-friendly documentation for CLI tools and APIs?▼

Yes, agent-friendly documentation restructuring applies to libraries, APIs, CLI tools, frameworks, and services to ensure key facts are accessible from plain-text entry points.

Why does my coding agent struggle to use my library?▼

Your project likely lacks capability signaling and structured documentation indexes, forcing the agent to rely on interactive navigation or rendered pages it cannot easily parse.