ai-contribution-readiness-audit

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.

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.

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.

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.

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.