AI-Coding-Guidance-Skills Development Patterns

Standardize Python feature implementation by enforcing kebab-case naming, relative imports, and named export conventions, while tracking progress in feature JSON artifacts. This ensures new modules blend seamlessly into the existing codebase and maintain consistent tracking.

Automate Conventional Commits messaging and feature tracking by coordinating feature implementation with task state updates via JSON artifacts. This workflow standardizes contributor messaging and mirrors progress directly in the repository's tracking files.

Run a semantic review and fix cycle to expand test coverage by following repeatable patterns for validating Python modules. This workflow provides a structured review, fix, and validate loop to ensure comprehensive test updates for new capabilities.

Yes, this development pattern workflow requires Python modules to use relative imports and named export conventions. Enforcing these specific coding conventions alongside kebab-case file naming guarantees that new kernel additions integrate smoothly.

Update feature JSON artifacts during iterative improvement cycles whenever delivering new capabilities, expanding coverage, or completing review-fix remediation. This maintains accurate task and feature state tracking across the repository.