antivibe

# AntiVibe - Code Learning & Audit Framework ## Purpose AntiVibe generates **learning-focused explanations or architectural audits** of any code — AI-generated, legacy, or otherwise. It helps developers understand: - **What** the code does (functionality) - **Why** it was written this way (design decisions) - **When** to use these patterns (context) - **What alternatives** exist (broader knowledge) Works on any codebase — you don't need recent git history or AI-authored files. ## When to Use Use AntiVibe when: 1. **Manual invocation**: User types `/antivibe` or "deep dive" 2. **Post-task learning**: After a feature/phase completes, user wants to learn from it 3. **Legacy codebases**: User wants to understand existing code they didn't write 4. **Proactive**: User says "explain what AI wrote", "walk me through", "audit this", or points at a file/directory ## What AntiVibe Produces Output saved to `deep-dive/` folder as markdown: ``` deep-dive/ ├── auth-system-2026-01-15.md ├── api-layer-2026-01-15.md └── database-models-2026-01-15.md ``` The exact sections depend on the output mode (see [Output Mode](#output-mode)): | Section | `compact` (default) | `full` | |---------|:---:|:---:| | **Overview** — what the code does and why it exists | ✅ | ✅ | | **Key Components / Concepts** — design patterns, algorithms, CS concepts used | ✅ | ✅ | | **Code Walkthrough** — file-by-file, line-by-line notes | — | ✅ | | **Learning Resources** — curated docs, tutorials, videos | — | ✅ | ...