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agent-readiness

Assess repository readiness for autonomous AI agent development across nine pillars.

1|Updated Mar 7, 2026
Search Tags:#AI development#autonomous agents#development lifecycle#repository assessment#codebase evaluation
One-click install
npx skills add https://github.com/cosmoscalibur/agent-hardness --skill agent-readiness-cosmoscalibur
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-readiness
Source: https://github.com/cosmoscalibur/agent-hardness/tree/main/skills/agent-readiness
Command: npx skills add https://github.com/cosmoscalibur/agent-hardness --skill agent-readiness-cosmoscalibur

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill assesses a repository's readiness for autonomous AI agent development, identifying areas that require improvement for smooth integration and operation.

Core Features & Use Cases

  • Repository Readiness Assessment: Evaluates against 9 pillars covering style, build system, testing, documentation, development environment, observability, security, task discovery, and experimentation.
  • Automated Scoring: Assigns a level based on the percentage of criteria passed, guiding improvement efforts.
  • Documentation Strategy: Recommends documentation improvements for human and AI agents, including README, docs/ directory, and agent context files.

Quick Start

Run the agent-readiness skill with the following command: agent-readiness --project-type <type> --repo-type <type>

Frequently Asked Questions about agent-readiness

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

FAQPage Schema
How do I evaluate if my codebase is ready for autonomous AI agent development?▼

Repository readiness for AI agents is evaluated across 9 pillars including style, build system, testing, documentation, and security. This assessment identifies compliance gaps and improvement areas needed for smooth automated agent workflows.

What is autonomous agent development lifecycle readiness?▼

Autonomous agent development readiness measures how well a repository supports automated workflows. It evaluates whether codebase practices align with best practices across 9 pillars, ensuring AI agents can discover tasks, experiment, and operate without manual intervention.

How do I assess repository compliance for automated agent workflows?▼

Assess repository compliance for automated agent workflows by running an automated scoring system against a comprehensive set of criteria. It assigns a readiness level based on the percentage of criteria passed, guiding targeted improvement efforts.

Does repository evaluation for AI development include documentation strategy?▼

Repository evaluation for AI development includes a documentation strategy that recommends improvements for both human and AI agents. It assesses the README, docs/ directory, and agent context files to ensure automated agents have necessary operational context.

What development pillars are checked during a codebase evaluation for AI agents?▼

A codebase evaluation for AI agents checks 9 development pillars: style, build system, testing, documentation, development environment, observability, security, task discovery, and experimentation. This comprehensive coverage ensures readiness for autonomous operations.

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