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claude-teams-brain
claude-teams-brain/start.mjs

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Readme

claude-teams-brain

Persistent memory for Claude Code Agent Teams
Your AI teammates remember what they built last session.

The Problem

Agent Teams are powerful — but ephemeral. Every teammate spawns blank. Your backend agent spent two hours learning your conventions and building auth. Tomorrow, a new backend agent starts from zero.

Meanwhile, a single npm test dumps 20,000 tokens of passing tests into context.

The Fix

claude-teams-brain hooks into the Agent Teams lifecycle to:

Remember everything — tasks, decisions, files, all indexed per role
Inject memory automatically — when backend spawns, it receives everything past backend agents did
Filter command output — 60+ command-aware filters cut token usage by 90–97%

No extra prompting. No manual context. Your team gets smarter every session.

Install

One command:

npx claude-teams-brain

Or with curl:

bash <(curl -fsSL https://raw.githubusercontent.com/Gr122lyBr/claude-teams-brain/master/claude-teams-brain/scripts/install.sh)

Then restart Claude Code.

Optional: Enable Agent Teams in ~/.claude/settings.json:
{ "env": { "CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS": "1" } }
Without this, the plugin runs in solo mode — memory still builds from your own sessions.

How It Works

Session 1                              Session 2
─────────                              ─────────
You: "Build payments module"           You: "Add refund support"

  backend agent spawns (blank)           backend agent spawns
  ↓                                      ↓
  builds Stripe integration              🧠 Brain injects memory:
  creates controller.ts                    • Past work: Stripe integration
  decides: use PaymentIntents API          • Files: controller.ts, stripe.service.ts
  ↓                                        • Decision: use PaymentIntents API
  🧠 Brain indexes everything              • Rule: all endpoints need auth
                                           ↓
                                         picks up exactly where it left off

Lifecycle Hooks (7 Events)

Hook	What happens
`SessionStart`	Brain initializes, warms up KB (CLAUDE.md, git log, dir tree)
`SubagentStart`	Role-specific memory injected directly into each new teammate
`TaskCompleted`	Task indexed immediately on completion
`SubagentStop`	Rich indexing: files touched, decisions made, output summary from transcript
`PreToolUse`	Injects general context for solo mode tasks
`TeammateIdle`	Passive checkpoint
`SessionEnd`	Full session compressed into a summary entry

Output Filtering

Every command through the brain's MCP tools is filtered before entering context:

Command	Before	After	Savings
`git push`	Transfer stats, compression, deltas	`ok main`	98%
`npm install`	Warnings, progress bars, funding	`added 542 packages in 12s`	90%+
`pytest` (all pass)	Full session output	`15 passed in 2.34s`	82%
`npm test`	20,000 tokens of passing tests	Summary + failures only	90%+

60+ commands supported. Raw output is always preserved in the searchable KB — only the filtered version enters context.

MCP Tools

Five tools exposed to all agents, designed for token efficiency:

Tool	Purpose
`batch_execute`	Run multiple shell commands, auto-index output, search with queries — all in one call
`search`	Query the session knowledge base built by batch_execute or index
`index`	Manually store findings/analysis for later retrieval
`execute`	Run code in sandbox (shell, JS, Python). Auto-indexes large output when `intent` is set
`stats`	Show session context savings metrics

Standard workflow: batch_execute → search → index

Quick Start

Existing repo:

/brain-learn

Scans your git history and auto-extracts conventions, architecture, file coupling, and hotspots. Zero config.

New project:

/brain-seed nextjs-prisma

Loads pre-built conventions. Profiles: nextjs-prisma, fastapi, go-microservices, react-native, python-general.

Then just use Agent Teams normally. Memory builds automatically.

Commands

Command	Description
`/brain-learn`	Auto-learn conventions from git history
`/brain-remember <text>`	Store a rule injected into all future teammates
`/brain-forget <text>`	Remove a stored memory
`/brain-search <query>`	Search the brain knowledge base
`/brain-query <role>`	Preview what context a teammate would receive
`/brain-export`	Export knowledge as `CONVENTIONS.md`
`/brain-stats`	Full stats: memory + KB + filter savings
`/brain-runs`	List past sessions
`/brain-replay [run-id]`	Replay a past session as narrative
`/brain-update`	Pull latest version

Key Features


Cross-session memory	Indexes tasks, decisions, and files per role across sessions
Output filtering	60+ command-aware filters, 8-stage pipeline, specialized parsers
Auto-learn	`/brain-learn` bootstraps the brain from your git history
Session KB	`batch_execute` auto-indexes output into searchable knowledge base
Solo mode	Works without Agent Teams — memory builds from your own sessions
Fully local	SQLite, no cloud, no telemetry, zero external Python dependencies
Cross-platform	macOS, Linux, WSL2, native Windows — all hooks run via Python

Architecture

All data is local in ~/.claude-teams-brain/projects/<hash>/brain.db (SQLite + FTS5).

7 lifecycle hooks capture everything → role-based memory → ranked + deduplicated → injected within a 3000-token budget.

For full technical details, MCP tool reference, and troubleshooting, see the full documentation.

License

MIT