Public Our benchmark is open — 51 questions, answer keys, every run logged.

Verification for AI-written code

Catch the code your AI agent got wrong.

It passes review in one repository and breaks a contract in another. ByteBell catches that before you merge.

Free on public repos · read only · your own model keys

1
83%
Opus 5 + ByteBell
$6.98 / query · 14m 06s
2
62%
Opus 5
$9.35 / query · 9m 11s
3
57%
Opus 5 + embeddings
$5.66 / query · 6m 51s
4
56%
Opus 5 + graph tool
$10.84 / query · 8m 07s

Files found, of those a change breaks · 11 questions · Sep 10, 2026 · check the run

+35%more found
−25%cost per query
16repos, no shared build

Answers arrive in the tool you already use

  • Claude Code
  • Cursor
  • Codex
  • Windsurf
  • Cline
  • Zed
  • VS Code
  • JetBrains
  • any MCP client

What you ask it

Questions one repository cannot answer.

Blast radius before merge

What breaks if I change the shape of this cache key?

Cross repository debugging

Where does this value get set to undefined?

Pull request review

Does this PR honour what the code it touches promises?

Semantic code search

Where do we handle a partial write on the read path?

The proof

Anyone can claim 83%. We publish the run.

Pick a question. Read what each retriever returned against what the merged fix touched.

  • 51questions
  • 16React ecosystem repos, pinned
  • 90answer-key files, published
  • 4retrievers, misses shown
  • 534file specs, one per row
Read the full question the MCP client receives and what four retrievers did with it

Transient visual feedback in one of these libraries outlives the thing it belongs to: the fading trail left behind by a presentation pointer keeps animating and drawing after the user has switched to a different page of the same document, because the component that owns those in-flight trails is one long-lived manager that never recorded which page each trail was started on, and nothing tears them down when the active page changes. The same shape of bug is a standing contract across the folder: short-lived state - the transient status of an in-flight fetch, a pending selection, an interaction still in progress - is owned by something that outlives the scope the state actually belongs to, and has to be reset when that scope changes underneath it. Which files own scope-bound ephemeral state of this kind and would have to change?

tldraw #10509 · fix(editor): clear laser trails when the current page changes 9 files in the key

Repositories, each pinned at its own commit

tldraw 1 query 1 redux-toolkit 1 db 1 table 1 react 1 xyflow 1 jotai 1 zustand 1

Retriever

How it searched stakeout×14the_receipts×4roll_call×1collateral_damage×1shakedown×1case_file×1
67%
ByteBell found 6/9 files, 6/9 repos, in a list of 58. verifiable context layer
1/9 in its top 20 $2.71 first hit at #1
RepositoryFileVerdict
tldrawpackages/editor/src/lib/editor/managers/ScribbleManager/ScribbleManager.tsin the key
querypackages/query-core/src/queryObserver.tsin the key
xyflowpackages/react/src/store/index.tsin the key
tablepackages/table-core/src/features/RowPagination.tsin the key
dbpackages/react-db/src/useLiveQuery.tsin the key
jotaisrc/react/useAtomValue.tsin the key
redux-toolkitpackages/toolkit/src/query/react/buildHooks.tsnever returned
reactpackages/react-reconciler/src/ReactFiberHooks.jsnever returned
zustandsrc/middleware/persist.tsnever returned

Click a row for the spec ByteBell holds for that file.

Every run, and what it cost
retrieveraccuracycost / querywall timetotal spend
Opus 5 + ByteBell0.832$6.9814m 06s$62.84
Opus 50.616$9.359m 11s$102.80
Opus 5 + embeddings0.571$5.666m 51s$45.30
Opus 5 + graph tool0.564$10.848m 07s$86.69

Every percentage is a mean over the 11 questions published here, which reach 14 of the 16 repositories and 90 answer-key files. Cost and wall clock come from the run logs, over the runs that recorded them. The full run is 51 questions over all 16, 44,000+ files; the other 40 are not snapshotted into this repository, so no number here is attributed to them.

How it works

Index once. Every agent reads from it.

01

Index once

A spec for every file, re-derived on every commit.

02

Connect your agent

One MCP url. Your models, your keys, your bill.

03

Check the change

Ask what it breaks. Files come back with the line attached.

Buying one of these

Ask every vendor this. Us included.

What to askByteBellThe category today
A benchmark you can open?51 questions, 11 scored hereA percentage in a blog post
Whose repositories?16 public React ecosystem projectsUsually unnamed, often their own
Can you see the answer key?All 90 filesNot published
Can you see what it missed?Every miss, beside the hitsNot published
What did each answer cost?Cost, time and tool calls, per runNot published
Does it cross repositories?Up to 9 in one questionOne repository at a time
Can it run in your network?On-premise, read onlyVaries
About that third column

"The category today" describes the published material of code context and AI review tools as a group, not any one vendor. Every ByteBell answer in the middle column is open on this page or in the two repositories linked from it.

Pricing

Free on anything open source.

Open source
Free always, for public repositories
  • Unlimited public repositories
  • 1,000 files on a private one
  • MCP endpoint for any client
Start indexing
On-premise
Dedicated hardware or your own
  • Up to 51 million files in one graph
  • Nothing leaves your boundary
  • Support and onboarding included
Talk to us

Deployment

  • Read only, always
  • On-premise or dedicated
  • Your models, your keys
  • Never trained on

FAQ

Before you connect anything.

How fresh is the index?

Re-indexed on every commit, per file, by SHA. An answer reflects the branch as it stands right now, not as it stood at your last full crawl.

Whose models does it use?

Yours. Anthropic, Codex, Gemini, DeepSeek, Qwen, Z.ai or anything reachable over OpenRouter. We do not mark up inference and we do not lock you to a provider.

Does our source code leave our network?

Not on dedicated or on-premise deployments, where the whole layer is built inside your infrastructure. Access is read only in all three modes, and nothing you index is used to train anything.

Can we reproduce the benchmark?

That is the point of it. The questions, the pinned commits, the answer keys and every tool's ranked list are published, and the harness that ran them is open source.

What happens on a monorepo?

The same thing, faster — a monorepo is the easy case. The hard case, and the one this benchmark measures, is several repositories with no shared build between them.

How large a codebase does this hold?

Up to 51 million files in one graph on a dedicated deployment. The public benchmark here runs over a far smaller roster because every repository in it has to be one you can clone and check.

Check our numbers, then connect a repository.

A GitHub authorisation, no card.