Understand your codebase without paying your agent to rediscover it.

Repowise indexes your code, dependency graph, git history, tests,
documentation, and decisions once, then gives agents and developers cited answers,
change impact, and concrete code-health fixes.

−31.6%	97.2%	2.3×
less agent output 3.8 vs 7.2 tool calls n=43 · p<0.0001	smaller context payload 393 vs 13,984 tokens 30 Flask commits	more defects surfaced same 20%-of-lines budget 2,770 files · p=0.003

_{Graph accuracy leader at matched coverage.
No tool finding as much was more precise in all 7 compiler-graded cells.
5 tools · 37,853 oracle edges}

_{Zero LLM calls for graph, risk, health, tests, dead code, and PR review. Generated prose is optional. Every benchmark publishes its sample, method, limitations, and losing rows.}

_{Free and self-hosted · core analysis stays on your infrastructure · no API key needed · AGPL-3.0 or commercial}

Why Repowise · Agents · Changes · Code health · Workspaces · Evidence · Enterprise · Docs

One index. Three ways to use it.

These are not disconnected scanners. The graph locates what git history flags; code health measures it; tests show what guards it; decisions explain why it exists; and the same evidence reaches your agent, editor, pull request, local dashboard, and cross-repository system map.

_{A dashboard tour recorded on this repository. The same local index powers the UI, MCP tools, editor views, and PR analysis. No API key and nothing uploaded.}

Pick your front door

Start in minutes (no API key)

pip install repowise
cd /path/to/your/repo
repowise init --no-prose -y
repowise serve

That builds the graph, git, decisions, health, dead-code and structural-wiki layers locally. Connect Claude Code, Codex, Cursor or any MCP host, or open the dashboard. init wires Claude Code automatically. Then ask your agent: "Use Repowise get_overview to summarize this repository" or "What breaks if I change src/auth.py?"

Full setup, every agent, and optional model-written prose →

Your agent stops guessing

Every question your agent asks about a repository has an answer that could have been computed ahead of time. Who calls this function? What breaks if I change it? Why is it written this way? Which files are actually dangerous? Without an index, the agent rediscovers that answer on every task: grep, read, re-read, forget.

Repowise exposes ten task-shaped MCP tools to Claude Code, Codex, Cursor, VS Code and anything else that speaks MCP: graph, git, docs, decisions, and ten MCP tools behind one index. See the canonical surface. Most tools are built around data entities (one file, one symbol), which forces agents into long chains of sequential calls. These are built around tasks: pass several targets in one call, get complete context back.

Because the exploration work is already done, that phase mostly disappears. In a measured agent loop across 43 questions on django/django, Repowise cut the agent's own output by 31.6% (p<0.0001) and reached the answer in 3.8 tool calls instead of 7.2. That is the end-to-end result.

One mechanism is much larger but narrower: loading a commit's context through get_context costs 393 tokens instead of 13,984, or 97.2% less. That is one retrieval payload, not a claim of 97.2% total agent savings. Both measurements and every competitor row are published in the benchmark report.

And it arrives without being asked. Optional hooks push context into the session at the moment it matters: the governing architectural decision when your agent edits a file that decision covers, a warning when it touches a file with a run of recent bug fixes, a compact briefing at session start. Repowise also generates your CLAUDE.md and AGENTS.md from the real index, so even an agent with no MCP support starts informed.

It learns from how you actually work. Repowise reads your own agent transcripts for the corrections you keep making ("use the shared HTTP client, not raw requests") and turns the durable ones into tracked decisions it delivers back later. The wiki generation budget tilts toward the modules you and your agent ask about most. All local, all deterministic, no extra LLM calls.