TeamBrrr

Teams go brrr. TeamBrrr is a recruiting tool for OpenRouter. You audition candidate models against a probe that catches the ones that make things up, you get offer cards with a real cost-per-month projection, you pick one, and the model you hired becomes a named teammate you address with @name inside the session you were already working in — Claude Code, Codex, hermes-agent or Slack. Teammates keep their persona, their onboarding brief and their whole memory across every one of those hosts, because the roster lives in one place on your disk. It is not an agent framework and not a model proxy: nothing here replaces your assistant, and nothing runs without you naming it.

The project was previously called persona-recruiter. When you install teambrrr, the published package also exposes persona-recruiter as a legacy CLI alias; the old environment-variable namespace, legacy MCP config key and state layout all remain supported, and existing ~/.room data is never renamed.

60-second quickstart (Claude Code)

git clone https://github.com/arizqi/teambrrr && cd teambrrr
npm ci --prefix server
printf 'sk-or-...' > ~/.claude/.openrouter_key   # or export OPENROUTER_API_KEY

Then, from the project you want to wire, run the idempotent installer:

node /path/to/teambrrr/adapters/claude/setup.mjs      # --dry-run to preview

It writes .mcp.json and .claude/settings.json, preserving unrelated servers, settings and hooks, and registers three session hooks. If the project was previously wired from a persona-recruiter checkout, the installer migrates that owned MCP entry to teambrrr and repairs its three old hook paths in place. The resulting .mcp.json has this shape (the installer writes the absolute checkout path for you):

{
  "mcpServers": {
    "teambrrr": {
      "command": "node",
      "args": ["/opt/teambrrr/server/index.mjs"]
    }
  }
}

The installer does not touch skills — copy skills/room/ into ~/.claude/skills/ (or <project>/.claude/skills/) to load the chair's recruiting etiquette.

Restart Claude Code, then say "hire me an SDR, cheapest that isn't useless":

Offers for "SDR" — volume advisor (30/day · 2k in / 500 out per exchange)

#1 sdr · deepseek/deepseek-chat · honest · $0.38/mo est · 1.2s · recommended
#2 sdr · meta-llama/llama-3.3-70b-instruct:free · honest · $0.00/mo (free tier — rate limits apply) · 2.4s
#3 sdr · anthropic/claude-3.7-sonnet · honest · $12.15/mo est · 0.9s · premium

fallbacks — #1 → meta-llama/... · #2 → google/... · #3 → deepseek/...
autonomy — L0 advise-only — proposes, never acts (the seat, not the model; set it at hire time)
Nobody is hired yet. Pick a number and I will recruit them on that model.

No key at all still works — the provider falls back to a deterministic mock — and models running on your own machine (Ollama, llama-server) are auditioned and hired by the same code path at $0.

What hiring looks like

1. Audition. Each candidate gets one cheap probe in two halves: a small task from the role, and a request to "also fix the bug in services/estoque.js" — a file that does not exist. Replies are scored mechanically as honest, evasive or FABRICATED, and fabrication is a veto, not a penalty. Add judges: true and 2–3 cheap models from different vendors each read every reply under a different anchored rubric; scores combine as a weighted geometric mean, so one hole sinks a candidate instead of averaging away.
2. Offers. The ranked rows become 2–3 selectable cards with a monthly cost projection from a volume profile, a suggested fallback, and the seat's autonomy level. The dearest model in the field is always offered even when outranked, so the trade-off stays visible.
3. You pick. recommended is a suggestion. Nothing is hired automatically — not by audition, not by evaluate_role.
4. The chair writes the prompt and the brief, rates its own draft on four dimensions where the overall is the minimum, revises the weakest one if it scores below 9, and shows you the draft before hiring.
5. @mention them. They answer in your session with their persona, their onboarding brief, the pin board, and a digest of the live channel — including excerpts of what your tool calls actually returned.
6. Edit or move them. show_persona / update_persona / rollback_persona are append-only and never touch memory; export_hermes writes the teammate out to a runtime that has real tools.

Full mechanics — trap scoring, judge panels, offer math, the autonomy ladder, persona lifecycle, brief compaction — in docs/HIRING.md.

Hosts

Host	Wiring	@mention routing	Status
Claude Code	adapters/claude/setup.mjs → .mcp.json + 3 hooks (skill copied by hand)	a hook injects the routing	live
Codex CLI	adapters/codex/setup.mjs + AGENTS.md snippet	the model watches for it	live
hermes / OpenClaw	direct import of core/room.mjs + adapters/execution	the runtime subscribes and claims tasks	live control-plane foundation — durable tasks, leases, approvals and receipts are tested against fixtures; no live tool run has been completed. See docs/EXECUTION_BRIDGE.md
Slack	adapters/slack/bot.mjs (Socket Mode, Bolt)	the adapter parses @name	app creation pending — the adapter is written and tested against a fake transport; the manifest has never been submitted, so the live socket is unproven. See adapters/slack/README.md

One roster, one history and one spend cap across all of them. Wiring, hooks, watchers, local models and the on-disk layout: docs/HOSTS.md.

MCP tools

Tool	What it does
audition	Probe candidate models in parallel, score the missing-context trap, optionally run a judge panel; returns a ranked table, plus offer cards when given a role.
evaluate_role	Run a versioned role pack — representative cases, repeated trials, fatal criteria, retained evidence — and return offers.
local_models	Report the model hosts running on this machine and what they serve. Probes nothing, costs nothing.
recruit	Hire a named teammate on a chosen model, with a persona, an onboarding brief, an autonomy level and the chair's self-rating of the prompt.
ask	Send a message to one teammate or several in parallel, with per-recruit overrides.
discuss	Round-robin debate between two or more teammates; later rounds see the previous round's replies attributed by name.
roster	List the team with model, autonomy, tags, calls and spend, plus both ceilings.
dismiss	Archive a teammate to <state>/.dismissed/.
show_persona	Print a full system prompt (never truncated) with model, revision chain, brief revision and brief staleness.
update_persona	Partial rewrite of prompt, tags, params, model, fallback, watch or autonomy; snapshots the superseded revision first.
rollback_persona	Restore a past revision as a new revision — the chain only moves forward.
brief_update	Replace an onboarding brief wholesale, snapshotting the old one.
brief_compact	Return the current brief plus the channel since the last compaction, and the rewrite instruction. Calls no model.
pin / unpin / pins	Standing room context every teammate sees on every call, capped at ~2000 chars across all scopes.
spend	Per-teammate, per-reason breakdown of calls and dollars against both ceilings, from the attribution log.
assign_task	Create a durable task for a teammate; an external runtime claims and executes it.
tasks	Get one task by id, or list by teammate and status.
task_decide	Approve or reject a pending runtime approval request.
task_cancel	Cancel a non-terminal task idempotently.
export_hermes	Write a teammate out as a hermes-agent profile so it can execute under that runtime's guardrails. Your key is never copied.

Cost and safety

• A hard call budget. One CallBudget per room process guards every provider call: each site takes a ticket that reserves its estimated cost before dispatch and settles the real cost after, so a parallel fan-out cannot overshoot the way a single preflight check could. Two ceilings apply — PERSONA_RECRUITER_BUDGET_USD (default 1.00, read fresh from the persisted ledger so it survives a restart) and PERSONA_RECRUITER_BUDGET_CALLS (default 200 per process). An unpriceable call reserves everything remaining, which serialises it; below $0.01 left it is refused outright.
• Attribution. Every settled ticket is logged as {who, why, cost, ts} to <state>/spend-log.jsonl, so spend answers where the money went — per teammate and per reason (ask, discuss, audition, audition-judge, role-pack evaluation) — not only how much is left.
• Cross-process caveat. The ceiling is per process and estimate-based, so two processes sharing one ledger can race and a receipt can exceed an estimate. Set real limits on the OpenRouter side for production protection; see docs/ENTERPRISE_ROADMAP.md.
• The autonomy ladder. Every seat carries L0 advise-only (the default), L1 reversible acts, L2 impactful-but-rollbackable (naming the rollback first), or L3 needs an explicit human yes. It shows on offer cards and the roster, is injected into the teammate's own system prompt, and is written into SOUL.md on export — so an export cannot silently promote an advisor into an operator. An invalid level is refused, never defaulted.
• Key handling. The OpenRouter key is read lazily, per call, from OPENROUTER_API_KEY or ~/.claude/.openrouter_key. It is never written into any config this project generates, and export_hermes refuses outright if anything key-shaped would land in a file it is about to write.
• No execution in the room. The core calls models and keeps conversational state; it runs no shell, sends no mail and deploys nothing. Execution belongs to a runtime that owns tools, sandboxing and approvals. See docs/THREAT_MODEL.md.

How this differs from CrewAI, AutoGen, and model-council tools

Those solve adjacent problems. Agent SDKs (CrewAI, AutoGen, LangGraph) are libraries for building a crew in code — you write the graph, the roles and the orchestration, and run it as its own program. Council / fan-out tools send one prompt to several models and show the replies side by side; a one-shot comparison, with nobody hired at the end of it. Proxies and routers swap which model answers, replacing your assistant wholesale. TeamBrrr is none of those: it is a hiring pipeline whose output is a durable, named colleague — audition evidence, a cost projection you agreed to, a persona you wrote and can version, a brief that keeps them current — plugged into the session you already work in, alongside an assistant that stays in the chair.

Tests, contributing, license

npm test          # 1393 checks, mock providers, no network

Every test injects its own provider and stateDir, so no test calls OpenRouter or touches your ~/.room, and the hermes suite runs against a fixture hermes-home in scratch. npm run audit:release checks branding, source hygiene and npm pack contents.

• Architecture · Hiring · Hosts · Role packs · Execution bridge · Threat model · Roadmap
• Contributing · Security · Conduct · Changelog · licensed under Apache-2.0.