codebase-exploration - SKILL.md Agent Skill

name: codebase-exploration description: > Use when exploring, understanding, or answering questions about a codebase that has Repowise indexed (a .repowise/ directory in the project root). Activates for "how does X work", "explain the architecture", "where is Y implemented", "what does this module do", or any task that needs an understanding of structure before diving into source files. user-invocable: false

Codebase Exploration with Repowise

This project has a Repowise intelligence layer. Before grepping and reading raw source to understand the codebase, reach for the Repowise MCP tools — they return documentation, ownership, history, decisions, and graph structure that plain file reads don't, usually in one round-trip instead of many.

Which tool for which question

You want…	Call
First orientation in an unfamiliar repo	`get_overview()` — architecture summary, key modules, entry points, git health, knowledge map. Skip it once you have the map.
A direct answer to "how/where/why does X work"	`get_answer(question="…")` — synthesised answer with citations + a `retrieval_quality` signal. Collapses the search → read → reason loop.
Find a symbol, file, or fuzzy concept	`search_codebase(query="…")` — hybrid search. `mode="auto"` routes an identifier to indexed symbol hits (`symbol_id`/line bounds → pipe into `get_symbol`), a path to file pages (→ `get_context`), and prose to semantic wiki search (each hit reports `search_method`: `embedding` vs `bm25`). Force a branch with `mode=symbol\|path\|concept\|hybrid`; narrow symbols with `symbol_kind`.
A triage card for specific files/symbols	`get_context(targets=[…])` — title, summary, signatures, hotspot bit, top callers, decision titles, symbol_ids. Batch many targets in one call.
The actual source of one symbol	`get_symbol("path/to/file.py::Name")` — exact bytes with line bounds. Cheaper than Read + offset math. Use a `symbol_id` from `get_context`.

Recommended flow

New area you don't know → get_overview() once.
A specific question → get_answer(question=…) first.
- High confidence → answer it, cite the paths.
- medium/low confidence → follow best_guesses[0].file or fallback_targets[0] into get_context, then get_symbol for bytes.
A named symbol or a path → search_codebase(query="Name") / search_codebase(query="path/to/file.py"); symbol hits pipe straight into get_symbol, file hits into get_context.
More files around a concept → search_codebase, then get_context on the hits (batched), then get_symbol only for the bodies you actually need.

Fall back to raw Read/Grep only when the indexed context doesn't cover the specific detail the user asked about.

Trust signals — verify when

_meta.stale_warning is present (the index has diverged from HEAD), or
retrieval_quality is partial/weak, or
a result's search_method is bm25.

Otherwise the response is current — act on it.

Error handling

"No repositories found. Run 'repowise init' first." → suggest /repowise:init.
get_answer/search_codebase come back empty → the repo may be in index-only mode (no wiki). Fall back to get_context with explicit paths, and note that full mode (/repowise:init with an LLM provider) unlocks docs + semantic search.
Tools fail to connect at all → the repowise binary may not be installed; suggest /repowise:init.