Every feature starts with three weeks of reading code.
Nobody can scope, estimate or review anything until someone works out what the system already does. ByteBell answers that from the code in minutes, with the file and the line attached.
The three weeks nobody puts on the roadmap.
spent working out what the system already does, before any code gets written.
the estimate they gave at the start, which is where teams report finishing.
extra scope found mid project, where a list of 120 items finished at about 170.
We read the codebase once, and everything else reads that.
To scope a feature.
Across four repositories, in one answer.
To trace a change end to end.
That run, against about $30 without it.
Cheap open source models read every file in your repositories, one time, at indexing.
Intent, contracts and cross repository dependencies, written in plain English with the file and line kept.
The extension in VS Code, plus Cursor, Claude Code and Windsurf over MCP.
What an agent writes gets compared to what the code promised, before it merges.
The whole product lifecycle, answered from the running code.
Six places a release loses time, and what each one looks like inside the extension.
Find out whether it already exists.
Teams rebuild things they already have. The code is usually there, behind a flag or in a closed pull request, and the person who knew about it has left. ByteBell checks the code, the pull requests and the docs before you spend a sprint on it.
bulk_export_v2, which has been off in every environment since March.The estimate starts from a file list.
Scoping happens in meetings because nobody in the room has the files open. Cross repository analysis gives you the list instead: every file the change touches, across every repository you have indexed, the team that owns each one, and the decisions it will not guess at.
Read your own system in plain English.
Most people will not read code to find out what it does. So ByteBell writes it out in plain English, file by file, with the line number on every claim. A product manager can read a service without opening an editor. An engineer can check any line of it in ten seconds.
This module adapts the vanilla store interface to React. It exposes one overloaded hook for the whole store or a selected slice, a bound store type, and a factory that supports default equality functions traditional.ts:1.
It supports reactive state management inside React applications. If it fails, components stop subscribing efficiently to shared state, and users see stale or excessive renders traditional.ts:22.
Identity is used as the default selector and the complete store state comes back. Undefined passes through the hook, or the factory applies its own default equality function traditional.ts:41.
Your agents write against the real contracts.
An agent without this layer reads whatever files it can reach and guesses at the rest. That is where the wrong code comes from. With the layer connected, it writes against the contracts your repositories already have, which is where the accuracy above 93 percent comes from. You keep your own keys and your own choice of model.
Nothing merges until it has been checked.
ByteBell traces what the change touches, writes tests for it, runs them, and then reviews each changed file against what that file promised before the change. Your senior engineers read the problems instead of the whole diff. The run below cost eleven cents.
The notes get written from what actually merged.
Release notes get written from tickets, so they do not match what shipped. The wiki drifts out of date one commit at a time, and the next feature gets scoped from a document that is wrong. ByteBell writes the notes from the merged pull requests and flags the pages that are now untrue.
Nobody taught me how to read a codebase. I was expected to already know.
The hard part of my first year has not been writing code. It is reading two hundred thousand lines of somebody else’s.
I read it for two days and still could not say whether changing line 400 breaks checkout. Nobody sat me down and taught me how to do this. It was assumed I arrived knowing.
The first four questions of the day are fine. The fifth one I swallow and guess instead, and the guess is what ends up in my PR. Nobody is keeping count. It feels like somebody is.
The actual reason is in a PR thread, a review comment and a ticket nobody linked. The diff tells me what changed. It has never once told me why.
I usually find out which one is true in review, in front of everybody. The page stopped being true eleven commits ago and nothing about it says so.
Three implementations exist. One is live, one sits behind a flag that never turned on, one is waiting to be deleted. Nothing in the repository marks which is which.
Checking the answer needs exactly the knowledge I was asking for. So I either trust it, or I go and read the code, which is the thing I was trying to avoid.
Nine weeks of work, three of them spent finding out what we had already built.
We got tired of it and built one index over our own code.
Every answer carries the file and the line it came from, so checking it takes ten seconds instead of trust. We point it at our own repositories first.
Play the demo: Why AI coding agents keep breaking production“Scoping used to be three weeks of meetings. Now the first meeting starts from a file list, and we argue about the two decisions that actually matter.”
The index updates on every commit. An answer reflects the branch as it stands right now, not last night's snapshot, which is the whole reason we trust it over our wiki.
Every language in common use. The gaps are the genuinely new and genuinely rare ones. Mojo, for example, is not supported yet.
Bring your own key. Anthropic, OpenAI Codex, Gemini, DeepSeek, Qwen, Z.ai, or anything reachable through OpenRouter. Your keys, your spend, your choice of model per workspace.
Hosted, on dedicated hardware, or fully on-premise inside your own network. On the second two, your source never leaves your infrastructure. Access is read-only in all three.
Index a thousand files before you decide anything.
Same index, same citations, same MCP connection on every plan. What changes is how many files it holds and whose hardware it runs on.
Enough for a service or a mid-sized repository. No card, and no feature held back.
- Every answer cited to a file and a line
- MCP connection to Cursor, Claude Code and Windsurf
- Your own model keys
2,500 files indexed, which in practice is three or four repositories. The point where a team stops asking one person what the system does.
- 2,500 files across your workspace
- Re-indexed on every commit
- Everything in Free
Runs inside your network. The index, the models you point it at, and your source all stay on infrastructure you control.
- Dedicated hardware or fully on-premise
- Anthropic, Gemini, Codex, DeepSeek, Qwen, Z.ai, OpenRouter
- Scoped to your repository count, not per seat
Start your next cycle from the code.
Point it at a repo. Discovery, scoping and specs all read from the same index, the way ours now do.