repowise
Codebase intelligence for AI and humans: code health scores, auto-generated docs, git analytics, dead code detection, and architectural decisions via MCP.

Codebase intelligence for AI and humans: code health scores, auto-generated docs, git analytics, dead code detection, and architectural decisions via MCP.
Independently written prompt templates for building AI coding agents, inspired by patterns observed in Claude Code codebase. System prompts, tool prompts, agent prompts, memory management, and multi-agent coordination.
Use when encountering questions about WHY code is built a certain way, when about to make architectural changes (new patterns,…
Use when reviewing a set of changes before they merge — a PR, a branch diff, or the working-tree changes you just made — in a…
Use when the user asks about code health, code quality, complexity, technical debt, which files are risky or hard to maintain,…
Use when exploring, understanding, or answering questions about a codebase that has Repowise indexed (a .repowise/ directory in…
Answer questions about a repository indexed on repowise.dev with the Repowise tools. Use when the user asks what a repository…
Defines practical standards for implementation-focused coding agents. Use when creating or editing code, especially when…
Use when the user asks about cleanup, removing unused code, refactoring, reducing bundle size, or identifying dead code in a…
Use before modifying, refactoring, or deleting files in a codebase that has Repowise indexed (indicated by a .repowise/…
Use before modifying, refactoring, moving, or deleting files in a Repowise-indexed repository, especially shared utilities, core…
Designs clear, testable prompts for agent workflows. Use when creating new prompts, refining weak prompts, or establishing…
Provides a structured verification workflow for code and prompt outputs. Use when asked to validate correctness, catch…
Ask a codebase question and get a cited, synthesised answer with a confidence rating (costs an LLM call).
Triage card for files, modules, or symbols — layer, hotspot, fix history, freshness (relationships, not source bytes).
Ingest or inspect test-coverage reports (LCOV, Cobertura, Clover, Go cover profiles, JaCoCo, Salesforce Apex JSON, or repowise…
Report unreachable files, unused exports, and zombie packages, tiered by confidence.
Work with architectural decisions — list, inspect health, add, or confirm auto-proposed decisions.
Diagnose the Repowise setup — install, API keys, index/store drift — and optionally repair it.
Export the wiki (or architecture model) to markdown, HTML, JSON, or Structurizr DSL.
Show Repowise code-health — KPIs, lowest-scoring files, refactoring targets, trends, or per-file markers.
Print the tests whose coverage intersects a change's changed lines — for a commit, base..head range, or staged diff.
Set up Repowise for this codebase. Installs if needed, asks about your preferences, and runs the indexing.
Rebuild the Repowise vector store by re-embedding all documentation pages. No LLM calls, only embedding API calls.
Rank a live change for review using a repo-relative percentile and an auditable supporting diff-shape score.
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