RoboCo is licensed under **AGPL-3.0** (see `LICENSE`). Copyright (c) 2026 Renzo Franceschini. Do NOT reintroduce an MIT or other license reference anywhere (README, headers, package metadata) — the project is AGPL.
Contributions require a signed **Contributor License Agreement** (`CLA.md`), automated via the CLA Assistant workflow (`.github/workflows/cla.yml`). The CLA preserves the option to dual-license / offer a commercial edition later; keep copyright assignment language intact. See `CONTRIBUTING.md`.
**RoboCo** is an AI Agentic Company - a virtual organization of 25 AI agents + 1 human CEO, designed to operate as a complete software development workforce. The system implements a structured organizational hierarchy with formal communication protocols, task management, and quality controls.
On a Python workspace, `WorkspaceService` runs `uv sync --extra dev` (not plain `uv sync`) so the clone's `.venv` carries the full gate toolchain (ruff/mypy/xenon/pytest) — the lint/type/complexity tools live in the `dev`**extra**, which plain `uv sync` skips. Without it an agent's `make quality` fails on `ruff: command not found` and the agent can't gate its own work.
The complete task lifecycle is defined in `roboco/foundation/policy/lifecycle.py` (`roboco/enforcement/task_lifecycle.py` is a backwards-compat shim over it):
**In-path PR-review gate** (`awaiting_pr_review`): each assembled PR is reviewed before the PM merges. The cell PM's `submit_up` opens the cell→root PR and the Main PM's `submit_root` opens the root→master PR; both enter `awaiting_pr_review`, where a reviewer `pr_pass`es it on to `awaiting_pm_review` or `pr_fail`s it back to `needs_revision` — the merge-level reject the PM otherwise lacks. Leaf dev tasks and branchless coordination roots skip the gate.
| `awaiting_pm_review` → `completed` | PM roles only |
| `awaiting_pm_review` → `awaiting_ceo_approval` | PM roles only |
| `awaiting_ceo_approval` → `completed/needs_revision/cancelled` | CEO only |
| Any → `cancelled` | PM roles only |
**Unclaim Operation**: Agents can release claimed tasks back to the pool using `unclaim()`. This transitions `claimed` → `pending` and optionally reassigns to another agent.
All tasks follow git workflow. PR is created BEFORE QA review (not after) so QA can review the real PR diff on GitHub and downstream PM/CEO approval chain off a PR that already exists:
Agents do not call the API or per-domain MCP tools directly. They go through two thin MCP servers (`roboco-flow`, `roboco-do`) backed by the server-side **Choreographer** in `roboco/services/gateway/`. The Choreographer composes the existing services (TaskService, JournalService, GitService, etc.) into intent-verb sequences. Tracing, claim-locking, evidence assembly, and remediation hints are all centralized there.
Each agent gets a **spawn manifest** at `/app/tool-manifest.json` listing the verbs its role is allowed to call. The orchestrator builds the manifest from `roboco/services/gateway/role_config.py` and mounts it read-only into the agent container.
Content tools (do_server) — most roles: `commit`, `note`, `say`, `dm`, `evidence`. Auditor is restricted to `note` (scope=reflect) + `evidence`. The `pr_reviewer` posts its change-request on the PR itself (no agent comms). The `prompter` (intake) and `secretary` are restricted to `note` + `evidence` — human-only, no `say`/`dm`/`notify`.
The `next` field tells the agent what to call next; the `remediate` field on errors tells them exactly how to fix and retry. Agents should not guess state — trust the response.
Agent backends are pluggable. `roboco/llm/providers/` defines an `AgentProvider` lifecycle ABC (`base.py`) and a `ProviderRegistry` keyed by `ModelProvider` (`registry.py`), with `ClaudeCodeProvider` (default) and `GrokCliProvider`. The orchestrator resolves a provider at spawn from the agent's `ModelProvider`; when no dedicated provider is registered it falls back to the built-in Claude Code spawn. `ModelProvider` (`roboco/models/base.py`) is `ANTHROPIC` (default), `GROK`, `LOCAL`, `OLLAMA_CLOUD`, `OPENAI` (reserved). The seam is additive: only `GROK` routes through `GrokCliProvider`; Anthropic / Ollama Cloud / self-hosted spawns are unchanged, and every provider gets the same MCP gateway + tool-manifest wiring by construction.
**Grok runtime.**`GROK` agents run xAI's official `grok` CLI (model `grok-build`) authenticated by a **SuperGrok subscription**, not a metered API key — so a Grok workforce can't stall mid-task on out-of-credits. The host `~/.grok/auth.json` is mounted **read-only** into each agent (`GrokCliProvider._append_grok_auth_mount`; `ROBOCO_HOST_GROK_DIR` is the host mount source, set up once with `grok login`). It reaches parity with the Claude path by construction: same MCP gateway + manifest, per-role tool-removal and git-operation deny rules, a prompt-injection guard on the task prompt, headless tool auto-approval, and per-agent token/cost capture from the grok session store. It covers both one-shot delivery roles and the interactive Intake (Prompter) and Secretary chats (per-turn `grok -p` with session resume).
**Token auto-refresh.** The grok access token has a fixed ~6h server-set TTL and the CLI cannot refresh it headlessly — on an expired token it hangs forever at an interactive login prompt. The orchestrator mints a fresh token from the offline-access refresh token (xAI's OIDC `refresh_token` grant) before expiry and rewrites the shared `auth.json` in place (`roboco/llm/providers/grok_auth.py``refresh_if_stale`, run once per dispatch tick; the orchestrator's `~/.grok` mount is read-write so it can rewrite it). As a backstop the agent entrypoint runs `python -m roboco.llm.providers.grok_auth --check` and refuses to start (exit 78) on a missing/expired token instead of hanging.
## Self-Healing & Feature Flags
**Self-healing CI loop (default-off).** RoboCo can watch its own repository's CI (a single named workflow) and, on a detected regression, open a fix task that is held out of dispatch until the CEO approves it (it terminates at `awaiting_ceo_approval`), then dispatch it through the normal delivery flow. It is dormant by default and armed by `ROBOCO_SELF_HEAL_ENABLED` plus a second opt-in `ROBOCO_SELF_HEAL_ORIGINATE_ENABLED`; origination is bounded by `ROBOCO_SELF_HEAL_MAX_OPEN_TASKS` / `_MAX_PER_CYCLE` so it can't flood the backlog. It never auto-merges or self-deploys (`roboco/services/self_heal_engine.py`).
**Feature flags / company-in-a-box.** Env-gated, default-off subsystems toggle from the panel's Settings → Feature Flags card (`panel/src/components/settings/feature-flags-card.tsx`) instead of hand-editing env: web research (`ROBOCO_RESEARCH_ENABLED`), the strategy engine (`ROBOCO_STRATEGY_ENGINE_ENABLED`), pitch provisioning (`ROBOCO_PROVISIONING_*`), external / internal PR review, the agent-runtime toolchain match (`ROBOCO_TOOLCHAIN_MATCH_ENABLED`), the architectural-conventions standard (`ROBOCO_CONVENTIONS_ENABLED`), and the self-heal flags above. A toggle persists in the settings store and takes effect on the next backend restart; an unset flag falls back to its environment / config default.
**Per-project architectural standard (default-off).** Beyond the `make`-style gates (which check syntax/types/tests, not *where code lives*), each project can carry a repo-canonical `.roboco/conventions.yml` — an architecture map (which definition *kinds* belong in which modules), a toggleable rule set, custom regex rules, and waivers — so an agent cannot land a Pydantic model defined inside a router or a `# noqa` / `# type: ignore`. Placement of a *helper* (any top-level function) only **warns** — too blunt to hard-block; `thin_routes` doesn't count an explicit `db.commit()`; and a small allowlist of unavoidable framework suppressions (ruff `TC001`–`TC003`, pydantic `prop-decorator`) is exempt. Gated by `ROBOCO_CONVENTIONS_ENABLED`; fully inert when off. RoboCo itself ships a canonical `.roboco/conventions.yml`.
**Effective map.** Consumers read the *effective* map — auto-derived defaults (from a repo scan + `BUILTIN_RULES`, excluding `tests/`/`docs/` trees) overlaid by the committed file — so behaviour is identical whether the file is present, absent, or partial. `ConventionsService` (`roboco/services/conventions.py`) builds it, caches it per `(project, HEAD sha)` in `project_conventions_cache` (migration `043`), renders the per-task baseline constraints + the ambient prompt block, and scaffolds/restores the file via a PR (`GitService.open_conventions_pr`). The committed file + scan are read from a dedicated project-level **read clone** the service ensures on demand (`WorkspaceService.ensure_read_clone`, pinned to the default branch's HEAD) — the backfill that makes the standard resolve even for a project created before it existed, with no manual `workspace_path`. The schema lives in `roboco/foundation/policy/conventions/` (pure).
**Validator.** A single Python CLI, `python -m roboco.conventions check --root <repo> --files <a> <b> ...` (`roboco/conventions/`), uses tree-sitter (Python + TypeScript grammars, shipped in the agent image) to classify each changed definition and flag forbidden placements + hygiene + custom-rule matches as JSONL findings, after waiver filtering. Precision over recall (it abstains when uncertain so a `block` gate can't false-positive-strand a task) and fail-loud (a validator that cannot run exits 3 so the gate blocks, never silently passes).
**Threading + enforcement.** The standard reaches the work two ways: an ambient "Architectural Standard" block injected at spawn (`compose_prompt`) and an auto-attached `## Constraints` section on every project task (`TaskService.create`). Enforcement is deterministic: a `block`-level finding refuses `i_am_done` (dev pre-submit) and `pr_pass` (the in-path PR gate) with the offending `file:line` + fix hint; findings also surface in QA's `claim_review` evidence (`convention_findings`). A false positive is relieved by a `waiver` the dev commits in their branch — accountable, reviewed in the PR. The panel's per-project Conventions tab (in the edit-project dialog) shows the map + health and offers Save / Restore.
The system runs as Docker Compose services. All Dockerfiles live under `docker/` at the project root; every service uses `context: .` plus `dockerfile: docker/<name>.Dockerfile`.
| `/ws/system` | Operator/system-wide stream (no per-agent keying) — the rate-limit lifecycle (`RATE_LIMIT_HIT` / `RATE_LIMIT_LIFTED`) and live usage (`USAGE_SNAPSHOT`, pushed to the usage dashboard) |
Server-side events reach these sockets through `roboco/api/websocket_bridge.py`, which subscribes to the `StreamEventBus` and forwards each event to the matching connections. To add a new live event: define an `EventType` (dotted value), publish it to the bus, add a `_handle_*` forwarder in `websocket_bridge`, and consume it on the panel via the `useWebSocket("/<endpoint>", …)` hook — do not stand up a parallel endpoint or client stack.
- **Provider rate limits** are tracked in Redis (`RateLimitStateTracker`, `roboco/services/gateway/`). On a provider 429 an agent calls `i_am_blocked(reason="rate_limited")`; the spawn gate then **queues** (never drops) further work for that provider, and a background probe-and-resume loop in the orchestrator clears the limit and revives parked agents when it lifts.
- **Provider overloads** reuse the same park-and-probe break. A persistent model-API overload (HTTP 529 / 500 / 503 — the SDK already retries transient ones) parks the provider exactly like a 429 instead of crash-retrying the agent straight back into the overload and burning tokens; the overload is detected orchestrator-side from the dead container's log markers, and the background loop revives the parked work when it recovers. Gated by `ROBOCO_OVERLOAD_BREAK_ENABLED` (default-on).
- **Gateway-health recovery** closes a blind spot in the stale-claim reaper: the heartbeat is bumped only by gateway verbs, so a broken-but-alive agent (a corrupted `/app/.venv` so no gateway tool imports) goes heartbeat-stale yet keeps its container up, and the reaper's live-skip would protect it forever. On a stale-heartbeat live container the reaper now probes the gateway out-of-band (`_probe_gateway_health` → `docker exec` the gateway venv imports) and, once broken past `ROBOCO_GATEWAY_HEALTH_GRACE_SECONDS` (a transient probe miss is tolerated), kills + evicts it (`_maybe_recover_broken_gateway`) so it falls through to release + respawn; healthy or inconclusive probes spare it. Gated by `ROBOCO_GATEWAY_HEALTH_ENABLED` (default-on). It is the third leg beside the shipped bash-guard `/app` block (prevents the self-corruption) and the reaper Docker-liveness fallback (stops over-reaping live containers).
- **PM coordinator concurrency.** A Main / Cell PM plans and delegates many root tasks in parallel — the actual work then runs in the delegated children/cells, not in the PM's own hands. The claim-time concurrency guards that keep a *developer* to one task at a time (`already_active` / `paused`, in `roboco/services/gateway/claim_guards.py`) are therefore **skipped for the coordinator PM roles** (`_COORDINATOR_ROLES = {main_pm, cell_pm}`, consulted in `_run_claim_guards`); only a genuine upstream **sequence dependency** (`unmet_dependency`, which parks the task back to `pending`) holds a PM's root back. Without this a single PM that claimed one root could never plan a second — it thrashed between its claimed roots and respawned forever, burning tokens for zero progress (the live `i_am_idle`-auto-paused-umbrella deadlock). The `paused` guard also excludes the target task itself, so a PM re-entering its own paused umbrella never self-blocks.
- **Token usage** is captured per agent session from the Claude Code transcript via the SDK server's `/usage/sync` (hook → orchestrator finalize → `agent_spawn_sessions` → `daily_usage_rollups` → dashboard). Cost uses provider-aware pricing in `roboco/billing/pricing.py` (Anthropic priced; local/Ollama intentionally `$0`). The token sweep also publishes `USAGE_SNAPSHOT` to `/ws/system`, so the dashboard's "Token Usage & Cost" panel updates live and falls back to HTTP polling when the stream is down.
- **Delivery observability** (the panel's Metrics → "Delivery" tab) shows how work *flows*, computed by `MetricsService` from data already captured — no new feature flag. Per-stage cycle time and the bottleneck distribution are reconstructed from the `audit_log` transition journey (each generic `task.<status>` event marks entry into a status; the named `task.qa_fail`/`task.pr_fail` events are excluded from the reconstruction). Rework rate reads `tasks.revision_count` — incremented once per transition into `needs_revision` at the single chokepoint `TaskService._emit_status_transition_audit` — and attributes each bounce to the QA / PR-reviewer via those named audit events; rework cost joins `agent_spawn_sessions.task_id`. Read-only endpoints: `/dashboard/metrics/{cycle-time,bottlenecks,rework,scorecard/agent/{id},scorecard/team/{team}}`.
The organizational structure, communication matrix, role descriptions, and access-control model are documented inline above and in the user-facing documentation site (MkDocs Material; source under `docs/`, built by `mkdocs.yml`, deployed by `.github/workflows/docs.yml` via GitHub Pages Actions and served at rennf93.github.io/roboco). `docs/rag/` remains the agent-facing RAG corpus (excluded from the published site); the old root `usage.md` / `deployment.md` are now redirect stubs into the site.