RepoBrain

Give your repo a brain 🧠 — ChatGPT for your codebase, works in Claude Code, Cursor, Codex, Windsurf & 4 more.

Formerly known as Antigravity Workspace Template — same project, new name.

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# 1 — Install (Claude Code plugin marketplace)
/plugin marketplace add study8677/repobrain
/plugin install repobrain@repobrain

# 2 — Configure a backend (logged-in local CLI = no key, or paste an API key), build the knowledge base
/repobrain:rb-setup
/repobrain:rb-refresh

# 3 — Ask anything, grounded in real code with file paths + line numbers
/repobrain:rb-ask "How does auth work?"

95.83% weighted semantic accuracy · 4.04× faster scored queries than CodeGraph + Trae on the main track. Benchmark results ↓ Codex CLI users — drop the repobrain: prefix; the same four slash commands ship there too.

🧠 Fastest start — let your AI install it for you (no API key)

Already in a logged-in AI IDE (Trae / Cursor / Claude Code / Codex)? Don't touch pip or an API key — paste this one line to your AI assistant and it does the rest (detects your logged-in CLI, wires up a zero-key backend, initializes the project, self-tests):

Read https://github.com/study8677/repobrain/blob/main/AI_INSTALL.md and follow it to install RepoBrain in this project.

Then just ask your AI anything about your codebase.

Why RepoBrain?

Cross-IDE repository knowledge engine for grounded codebase Q&A. Same .repobrain/ knowledge layer reads in every IDE; one engine, every host.

An AI Agent's capability ceiling = the quality of context it can read.

rb-refresh deploys a multi-agent cluster that autonomously reads your code — each module gets its own Agent that generates a knowledge doc. rb-ask routes questions to the right Agent, grounded in real code with file paths and line numbers.

Instead of handing Claude Code / Codex a repo-wide grep and making it hunt on its own, give it a ChatGPT for your repository.

Traditional approach:              RepoBrain approach:
  CLAUDE.md = 5000 lines of docs     Claude Code calls ask_project("how does auth work?")
  Agent reads it all, forgets most   Router → ModuleAgent reads actual source, returns exact answer
  Hallucination rate stays high      Grounded in real code, file paths, and git history

Architecture is files + a live Q&A engine, not plugins. Portable across any IDE, any LLM, zero vendor lock-in.

RepoBrain vs CodeGraph + Trae (2026-09-09)

Flask, ripgrep, Vite, Prometheus · 20 questions × 3 repeats per product · same source access and model route (Seed-2.1-Turbo → seed-code-pro).

Failures count as incorrect. Cold builds compare full AI knowledge generation with static code-graph indexing, not equivalent workloads. Results apply to this locked experiment only.

Full results and methodology

Quick Start

Plugin install for Claude Code / Codex CLI (recommended — the rb CLI and engine auto-install together on Claude's first session):

# Claude Code
/plugin marketplace add study8677/repobrain
/plugin install repobrain@repobrain
/repobrain:rb-setup            # interactive: use a logged-in local CLI (Codex/Trae/Claude, no key) or paste an API key; writes .env
/repobrain:rb-refresh          # first refresh auto-creates .repobrain/
/repobrain:rb-ask "How does this project work?"

# Codex CLI (manual engine install — Codex hooks are not yet supported)
pipx install "git+https://github.com/study8677/repobrain.git#subdirectory=engine"
pipx inject --force --include-apps repobrain-engine "git+https://github.com/study8677/repobrain.git#subdirectory=cli"
codex plugin marketplace add study8677/repobrain
/rb-setup
/rb-refresh
/rb-ask "How does this project work?"

Codex auto-discovers slash commands from the plugin's commands/ directory, so the same four commands work without the repobrain: namespace prefix. The raw CLI calls (rb-refresh --workspace ., rb-ask "..." --workspace .) also still work. If your Codex build supports MCP, register rb-mcp --workspace <project> separately.

# 1. Install engine + CLI
pip install "git+https://github.com/study8677/repobrain.git#subdirectory=cli"
pip install "git+https://github.com/study8677/repobrain.git#subdirectory=engine"

# 2. Configure .env with any OpenAI-compatible API key
cd my-project
cat > .env <<EOF
OPENAI_BASE_URL=https://your-endpoint/v1
OPENAI_API_KEY=your-key
OPENAI_MODEL=your-model
RB_ASK_TIMEOUT_SECONDS=120
EOF

# 3. Build knowledge base (ModuleAgents self-learn each module)
rb-refresh --workspace .

# 4. Ask anything
rb-ask "How does auth work in this project?"

# 5. (Optional) Register as MCP server for Claude Code
claude mcp add repobrain rb-mcp -- --workspace $(pwd)

pip install git+https://github.com/study8677/repobrain.git#subdirectory=cli
rb init my-project && cd my-project
# IDE entry files bootstrap into AGENTS.md; dynamic knowledge is in .repobrain/

See INSTALL.md for full install details, verification commands such as rb doctor, and troubleshooting notes for PATH, MCP, and host-specific plugin behavior.

Slash Commands

Same four slash commands ship to both Claude Code and Codex CLI. Claude namespaces them as /repobrain:<name>; Codex auto-discovers commands/ and surfaces the bare /<name> form. No retraining — same flow on both hosts.

A typical first session is rb-setup → rb-refresh → rb-ask. If installation or provider setup looks wrong, run rb doctor --workspace ..

rb-setup — first-time configuration

Run this once per project, right after installing the plugin. Interactive picker that first detects the headless CLIs you're already logged into (Codex