cld-md-improver

Auditing a CLAUDE.md file involves scanning for command availability, architectural clarity, non-obvious patterns, conciseness, currency, and actionability. This skill checks your repository's documentation against these specific quality criteria to provide a quality score and actionable recommendations for enhancing AI context.

Effective codebase documentation in a CLAUDE.md file requires available commands, clear architectural insights, non-obvious patterns, and actionable instructions. Maintaining these elements ensures the file provides optimal project context for AI models to understand and work within your repository.

Capturing session learnings into project memory involves consolidating key takeaways from a development session into a CLAUDE.md or .claude.local.md file. This skill supports proactively capturing these insights to optimize project memory and maintain documentation currency.

Yes, you can update outdated repository documentation by running a proactive audit. The skill identifies specific areas for enhancement and suggests concrete additions to ensure your CLAUDE.md file remains current, concise, and actionable for AI models.

Automated CLAUDE.md quality audits require adherence to specific quality criteria and update guidelines to be effective. The audit is limited to scanning for command availability, architectural clarity, and conciseness, meaning developers must still manually verify non-obvious codebase patterns.