ai-contribution-readiness-audit

Audit a repository's AI contribution readiness and generate concrete file changes.

Updated Mar 1, 2026

Search Tags:#code quality #automation #ai #developer tooling #contribution guidelines #repository audit

Ready to run

npx skills add https://github.com/corymhall/toolkit --skill ai-contribution-readiness-audit

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ai-contribution-readiness-audit
Source: https://github.com/corymhall/toolkit/tree/main/general/skills/ai-contribution-readiness-audit
Command: npx skills add https://github.com/corymhall/toolkit --skill ai-contribution-readiness-audit

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps ensure that software repositories are well-prepared for AI code contributions, leading to higher quality AI-generated code and more efficient development workflows.

Core Features & Use Cases

Repository Audit: Evaluates a repository's structure, documentation, and command availability for AI contribution readiness.
Concrete Fixes: Generates actual file content (e.g., AGENTS.md, PR templates, Makefiles) to address identified gaps.
Use Case: When AI-generated pull requests are consistently low quality or fail CI, use this Skill to diagnose the root causes and receive actionable steps to improve the repository's AI contribution environment.

Quick Start

Use the ai-contribution-readiness-audit skill to evaluate the current repository and produce a packet of file changes to improve AI readiness.

Frequently Asked Questions about ai-contribution-readiness-audit

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

FAQPage Schema

How do I audit my repository for AI code contribution readiness?▼

AI contribution readiness audits evaluate a repository's instruction contract, verification loop, safety rails, architecture clarity, task surface, testability, observability, contribution ergonomics, and anti-drift controls to diagnose why AI-generated pull requests fail.

What is AI contribution readiness and why do my AI-generated pull requests fail CI?▼

AI contribution readiness is a repository's preparedness for AI code contributions, determined by its documentation, safety rails, and command availability. When AI pull requests fail CI, poor readiness means the AI lacks the instruction contract and verification loop needed to generate valid code.

How do I fix a repository that produces low-quality AI-generated code?▼

To fix a repository producing low-quality AI-generated code, generate concrete file changes like AGENTS.md, PR templates, and Makefiles to address identified gaps in contribution guidelines, architecture clarity, and task surface, improving the overall AI engineering environment.

What files do I need to add to make my repository ready for AI-assisted engineering?▼

You need to add concrete, copy-pasteable files like AGENTS.md, PR templates, and Makefiles to make a repository ready for AI-assisted engineering. These files establish the instruction contract, safety rails, and contribution ergonomics required for high-quality AI code contributions.

Does improving repository documentation actually increase AI code quality?▼

Improving repository documentation increases AI code quality by providing a clear instruction contract and architecture clarity. An AI contribution readiness audit diagnoses documentation gaps and produces actionable file changes to ensure AI agents understand the repository's task surface and safety rails.