redhat-et/ripwire

For a single developer, this tool is a good lookup accelerator. For an orchestrated fleet, it's load-bearing: it

halved the research spend, twice redirected tasks before wasted work, prevented at least one silent-divergence shipped

bug, and turned code-quality hygiene from a hope into a per-task mechanical gate. Whole-workflow ~2×; per-lookup

10–25×; and two moments where one call was worth more than the rest of the session's tooling combined.

> — the report's bottom line

*The model's own report of one engagement, on a version before 0.5; not a controlled measurement. Controlled measurements are in docs/EVALS.md.*

Beside those sits a labelled survey of 237 tools that contributed nothing and says so. The two sets are disjoint by construction, so they add rather than nest — a tool that gave a lesson is never counted twice.

Both halves are load-bearing, and they are doing different jobs. The settled results are what make the quality lens trustworthy: McCabe on complexity (1976), Halstead on volume (1977), Spärck Jones on term specificity (1972), Nagappan & Ball on churn. Fifty years of replication means those are not opinions, and a tool that measures your code should be built on the ones that survived.

The recent work is what makes it current: seventeen of the folded papers are from 2026, seven published in the last two months and three in the last thirty days (dates as of 2026-09-08; every row carries its arXiv id, so the claim is checkable rather than atmospheric). Retrieval for coding agents, context-compression cost, placebo-controlled localization — that literature is months old, not decades, and several rows were folded within weeks of the paper appearing.

Neither half alone would be enough. A tool built only on the classics would not know what an agent needs; one built only on last month's preprints would have nothing underneath it. And the newest row is a result that failed when it was tested here — which is the point of writing them down. All three counts are re-derived from that document's own tables by test/readmedriftcheck.sh on every run, which fails if this page and those tables disagree, so the claim cannot quietly drift. The row-by-row ledger is docs/LINEAGE.md.

Measured on 48 matched questions across django, webpack and this repository. Across all three, ripwire indexes in 0.25–0.45 s and 6.6–16.5 MB against that server's 23–52 s and 391–623 MB. The full method, the wins named one by one and the losses included, is in Against the leading graph-database code-context MCP server and docs/EVALS.md.

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:

Two things make that reachable in practice, and neither is the destination. Answers are honest about their own limits — a count that cannot be a total is labelled a floor, a zero means "none found" and never "none exists", every truncation is disclosed — so an answer never looks more complete than it is, and the map never degrades the code by guessing. And an answer can be given a token budget, so what one costs is something you ask for rather than discover; where a complete answer will not fit, it says it went over rather than silently dropping the row you needed.

Those two are the stair-steps: honest about what is missing, priced in what it spends. The step they climb toward is a question fully answered in one call, which is not always trivial to reach — and where it is not, the output says so rather than pretending otherwise.

How we measure the climb. A complete answer to every code question is genuinely hard, and it is reached over many releases rather than in one. Until an answer can be complete, it owes you three things: it stays bounded in size, it is fully honest about what it does not know, and it gives you a clue where to look next. So every change is judged on more than "was it right":

• Complete answers: the share of questions answered so you can act without re-checking.
• Honest-partial rate: how often an incomplete answer says what it is missing, instead of

• False-confidence rate: wrong answers that claim to be complete — the worst case, held near zero.
• Next-clue usefulness: for partial and wrong answers, whether following the answer's first

Answering comes first; efficiency is how we get there. We aim for answers about as lean as the leanest tools, but a byte budget is never allowed to cost an answer. We have gone too far toward short answers before and cut information that was needed, so now every size limit has one of two jobs: a runaway guard far above typical answers (it catches an output bug, and says so when it trips), or a stair-step target where anything over it must be explained. A capped answer is always measured against the same answer uncapped, and the one that answers better wins.

Ten everyday moments, re-measured on this repository, 2026-08-08. Figures are ~tokens (≈ bytes/4); every ratio comes from a real run, reproduced by the command in its row — raw byte counts and exact commands in docs/EVALS.md §5.

These aren't summaries that gamble with information. Each row is scored same-correct-answer-or-it-doesn't-count, and both sides were checked, not assumed: orient surfaces this repo's own pipeline files (ingest.cpp, graph.h, serialize.h) in the first screen, the same three docs/ARCHITECTURE.md names as central; the --for row lands mcpStale (src/mcpindex.h:633), the actual staleness check, 5th-ranked; --recall lands the container-rule doc (AGENTS.md) that states, verbatim, the same "no std::map" rule CONTRIBUTING.md explains in full; --pack-task names the same three touch points a human would — cachelint.h, mergeCachePack (src/main.cpp:1787), the lintrules.h helpers it reuses; --expand --top-k=0 hands back the requested function's complete, unmodified body — the ranked-neighborhood addition costs the same ~22.6 KB regardless of which function you ask for, confirmed on two (a fixed floor, not per-function variance); --callers on langOfPath names its 2 real callers, the same ones a grep hit-list buries under 5 files of comment-only mentions; --impact+--uses on coversOrEquals names the same 2 direct call sites --uses alone would, plus (disclosed) a transitive reach --uses doesn't cover at all; --from-trace resolves all 7 frames of a real call chain by name to the same definitions a per-frame grep would eventually find, mixed with call sites and comments; --situ on a 2-file diff names the same 6 real test harnesses, 2 of which a filename grep across test/ cannot find even after opening every one of its 41 candidates — a completeness gap, not just a byte one; --pr-context surfaces co-change partners (test/regression.sh, src/main.cpp) a raw git diff has no way to know were usually touched and weren't this time — Fowler's Shotgun Surgery checked rather than merely named (the backtest is in docs/EVALS.md). The map ranks and discloses — it never paraphrases your code — and every truncation is disclosed in the header.

The honesty line, made concrete: the same auto-selection behind the --expand row also runs the other way. On a small file (pageRankDouble in src/pagerank.cpp, 5,559 B) the ranked bundle would cost 27,916 B — nearly 5× more than the file — so ripwire serves the file itself instead, disclosed as mode="whole-file" on the response, not silently. docs/EVALS.md §7 lists that and the other counterexamples this project publishes against itself.

The shape: plan the work, then run a loop that matches each task to the model that fits it. Every thread it spawns opens with an empty context on a repository it has never seen. Orienting an empty context to a large repository is the most repeated cost in the whole system, and the one this tool was built for — it is also the cost that grows with the size of the tree, which is why the pattern matters more the bigger the repository gets.

--for and --pack-task answer it in a single call, at the per-call rates in the table above, instead of a grep-and-read tour that every lane pays over again from scratch.

The return path matters as much. --quality-delta, --test-gate and --edit-check answer *what did I make worse*, which tests must run, did I change a contract — quantitative answers a lane can hand back as a verdict, rather than a transcript the orchestrator has to read to find out what happened.

What is and is not claimed here. Every figure on this page is a single-agent measurement. That the saving compounds with the number of cold orientations follows from the fixed-cost mechanism, but it is pre-registered and unrun — the reason the pattern is worth trying, not a result this project has published.