Rip'n Fast. Less Tokens. Better Code.

Give your coding agent a map before it reads the repo.

ripwire is the ripgrep of AI context. Point it at any repository and your agent gets a ranked, deterministic call graph — what to touch, what it breaks, which tests to run — instead of grepping around and reading whole files.

Languages: Rust · C++ · Objective-C/C++ · C · Metal · CUDA · Python · Go · Swift · TypeScript · JavaScript · Java · Ruby · PHP · Lua · Bash · C# · JSON · TOML · YAML · Markdown — twenty-one vendored grammars, and adding another is a vendored tree-sitter grammar plus one row in a declarative table.

No API key. No embeddings. No index server. No daemon.

One self-contained binary on your own machine, offline, installed in one line — and the same line installs and activates the task-shaped skills that teach your agent when to reach for it, not just how, for every agent it finds on the machine. If your agent can run shell commands — Claude Code, Codex, Cursor, Windsurf, Gemini, opencode, aider — it is set up the moment the install finishes; the MCP server is the optional second interface. Install it and ask it something before you finish reading this page:

RIPWIRE_REPO=redhat-et/ripwire bash -c "$(curl -fsSL https://raw.githubusercontent.com/redhat-et/ripwire/main/scripts/install.sh)"
ripwire . --for="incremental cache invalidation"

One deterministic, token-budgeted answer: the relevant symbols, their callers, the change risks, and the tests that reach them. Run on this repository (2026-08-30), that second line answers in about 4.3K tokens with:

• The ranked symbols, in rank order — the cache-header constant kCacheMagic first (with its doc comment quoted in place and the one next= call that opens it), then spanTierMemoPath (the cache-path composer), ingestCommitTree, … ingest — each row with its file, line, and signature.
• Risk, annotated in place — complexity, git churn (ingest shows 128 recent edits), change amplification (touch ingest and 266 graph nodes feel it), purity and test coverage. The fragile spots are visible before anything touches them.
• One-hop call context — spanTierMemoPath calls shaKeyedCachePath, headSnapRepoHex, exclConfigHex; no second query needed to see the neighbourhood.
• Its own confidence — this answer says confidence="high" with the score margin attached; a flat ranking says low, so it reads as a starting point instead of masquerading as an answer.

If it works on your codebase, tell us what it got wrong

Every number on this page is a measurement on a corpus we happen to have. Yours is one we don't.

After you have actually used it on your own repository for a while, hand your agent prompts/improve-for-my-language.md. It harvests that session's own transcript — where ripwire answered, where it missed, where you fell back to grep — and every finding it produces has to cite the moment it came from: what you asked, which command ran, what came back. Open an issue with the result.

That is worth more to this project than a bug report, because it arrives in the form the project already runs on: evidence with its provenance attached, not an impression. Several languages here are one contributor's corpus away from being measurably better, and we cannot see your code.

<ctx task="incremental cache invalidation" confidence="high" margin_pct="20"
     bundle="compact" bodies="0" reason="compact-route" est_tokens="3995">
  <sigs shown="23" total="40" capped="1">
    <d l="106" n="kCacheMagic" p="src/ingest_cache.h" cx="0" in="0" churn="11" amp="71" pure="1" r="1"
       next="--expand=src/ingest_cache.h:kCacheMagic">
      <doc>incremental cache (--cache): per-file content hash + raw facts so a
           re-run re-parses ONLY …</doc>constexpr std::uint32_t kCacheMagic = …</d>
    <d l="1307" n="spanTierMemoPath" p="src/ingest_astquery.h" cx="1" in="2" churn="5" amp="44" r="2"> … </d>
    <d l="247" n="ingestCommitTree" p="src/dmm.h" cx="6" in="1" churn="6" amp="27" r="3"> … </d>
    …
    <d l="191" n="ingest" p="src/ingest.cpp" cx="4" in="14" churn="128" amp="266" tested="1" r="13"> … </d>
    … </sigs>
  <hops shown="2" total="6" capped="1" noedge="2">
    <h l="1307" p="src/ingest_astquery.h" n="spanTierMemoPath">
      <calls total="3"><c n="shaKeyedCachePath" l="1621"/> … </calls></h> … </hops>
</ctx>

cx= complexity, churn= git edit frequency, amp= change amplification, r= rank; <hops> rows carry the one-hop call context, caps disclosed. Every attribute is defined in the one legend at the top of the real output, which also self-reports the bundle's cost — est_tokens="3995" here.

And against five retrieval competitors on a held-out LocBench slice, it finds all gold files in the top 10 on 58.3% of instances — the best alternative lands 40.0% — while indexing in 0.31 s. The full leaderboard, losses included ↓

See the map — not just the numbers

ripwire path/to/django/db/migrations --rank-by=rrf --top-k=120 --color-by=cx --html=map.html

One self-contained HTML file (--html[=FILE]), no server, no CDN, no external asset. --color-by=lang|community|cx|churn|tested sets the initial colour; the page embeds all five and keeps a live selector, so switching lens costs no second run.

Read from the figures above, which state their own rules in a sidecar saved beside each image:

• arrow points caller → callee — the graph is directed, and the page draws it that way.
• 31 of 183 shafts dashed in this view = the resolver could not choose between same-name definitions and split the call over all of them — per edge, not per symbol. A symbol-level "this function makes some ambiguous calls" would mark every one of its edges, which would be a lie about most of them.
• labels: top 24 by in-view degree, one per name — one label per distinct name, so a picture of a container class stops crowding out the functions you asked about.
• shapes: ● fn ■ cls ✚ var — kind is nominal data on a nominal channel; complexity never uses shape.
• module outlines: 7 of 12 modules with 3+ nodes in view (cap 12; 3 dropped as too thin to read as a region; 2 dropped as enclosing mostly other modules) — three separate truncations, each with its own count and its own reason.

The cx and churn ramps share one five-stop scale, ordered so lightness rises with the value — it survives greyscale printing, and every adjacent pair stays separable under protanopia, deuteranopia and tritanopia. Thresholds are fixed rather than per-corpus quantiles, so a hot node cannot be manufactured by a cold repository.

churn n