Bito?

NOT REALLYA prototype of the interface is possible, but the durable product depends on difficult systems beyond the UI. Build a safer adjacent workflow instead.

BUILD FIRST

A non-sensitive or read-only version of the core experience
A manual review step wherever correctness or trust matters
A narrow companion tool that removes a real piece of work

LEAVE FOR LATER

Regulated decisions, payments, or irreversible actions
Claims of correctness, compliance, or uptime that the MVP cannot support
Sensitive integrations until security, support, and auditability are ready

RESEARCH NOTES

What this tool actually does.

Checked 2026-09-06

Bito (bito.ai) is an AI developer-assistant platform. Its flagship product, the AI Code Review Agent, reviews pull/merge requests on GitHub (cloud and self-hosted), GitLab, and Bitbucket, posting line-level comments, PR summaries, and one-click fix suggestions that commit changes back to the PR. Bito says it understands code via symbol indexing, abstract syntax trees, and embeddings, and offers cross-repo impact analysis mapping touched services, APIs, and dependencies. Reviews can be fully automated or triggered by typing /review in a PR comment, are incremental across commits, and draw on 'specialized engineers' covering security, performance, scalability, and breakage risk. It merges feedback from static analysis, linters, OSS vulnerability checks, and secrets scanning, optionally validating PRs against linked Jira tickets. An org dashboard provides code-review analytics, custom revie

SOURCES

RESEARCHED BUILD PROMPT

Give this to your coding agent.

Build an original, from-scratch tool inspired by a distinctive Bito workflow: when a developer opens a pull request on GitHub, the tool automatically analyzes the diff plus relevant repository context and posts an actionable review. User-facing requirements: webhook-triggered reviews of open PRs; a PR summary comment; line-level review comments with suggested fixes that can be applied in one click via the GitHub API; a configurable custom guidelines file per repo (e.g., 'no magic numbers', naming rules); secrets and vulnerability scanning of added lines; per-repo enable/disable and LLM model choice; and a minimal dashboard showing PRs reviewed, issues found by category, and fixes accepted. Technical requirements: a service that ingests GitHub webhooks, fetches diffs and file contents via the GitHub API, builds a lightweight code index (tree-sitter AST + embeddings) to retrieve relevant symbols/context, calls an OpenAI-compatible LLM API with the diff plus retrieved context, and posts findings through the GitHub API; config/review history stored in SQLite or Postgres; auth via a GitHub App or PAT. Implementation approach: Node/TypeScript or Python (FastAPI) with a job queue (BullMQ or RQ/Redis), webhook endpoint, and worker. Explicitly do not copy Bito's brand, logo, marketing copy, proprietary assets, or UI; use original naming, visual design, and UX. Out of scope: GitLab/Bitbucket support, IDE plugins, Jira integration, billing, and per-user role analytics. Include a README covering local setup (ngrok webhook forwarding, env vars, DB migration, LLM API key), how a PR gets reviewed end to end, and important limitations: LLM cost and latency on large diffs, token truncation, false-positive reviews, GitHub API rate limits, and the risk of the language model echoing or leaking repository data.

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