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A system where AI agents review pull requests for code quality, consistency, security, and adherence to conventions.
A comprehensive approach to testing covering unit, integration, and e2e philosophy, what to test, and deployment confidence.
A specification for how code review should work covering what to look for, how to give feedback, and when to approve.
How to specify a codebase refactoring for an AI agent covering scope, safety constraints, and validation.
The official skill for turning a project, chat transcript, or folder of notes into a properly-structured BotDoc draft using your LLM.
Rules for human-AI collaborative coding covering delegation, review, and maintaining code ownership.
An automated system for generating and maintaining documentation from codebases including API docs and changelogs.
A system where raw source material is compiled by an LLM into a structured, interlinked markdown wiki with summaries, backlinks, and an auto-maintained index.