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.
Because the clone is shared across a dev's tasks, a **fresh claim** git-resets the workspace to a clean tree (`git reset --hard`) before checking out the new task's branch — discarding abandoned uncommitted cruft from a finished task while preserving all commits and the gitignored `.venv`. A resume short-circuits before this, so committed work is never reset.
A task has at most **one active WorkSession**: re-claiming a task (pool release, reaper unclaim, escalation redirect) supersedes any prior agent's stale active session, enforced both at the service layer and by a DB partial-unique index (migration 047). Without it, duplicate active sessions made the one-row active lookup raise and crashed the claim/plan flow into a respawn loop.
A developer's clone is shared across all their tasks, so push and PR-head operate on the task's **recorded branch by name**, independent of the clone's current checkout — fixing the `BRANCH_MISMATCH` / "No commits between" failures when the clone was parked on a later task's branch. A missing local task-branch ref is first recovered from `origin/<branch>` before the push-by-name.
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.
**Board never owns a coordination root**: a Board role (Product Owner / Head of Marketing) is never assigned a Main-PM coordination root (delivery root or MegaTask root-subtask) via escalation or reassignment — Board roles have no `unblock` verb, so such a hand-off would deadlock. The transition is diverted to the pool for a role-matched Main-PM reclaim.
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:
Agent learnings (`note` scope='learning') broadcast as knowledge-share notifications only to other **agents** — the human / human-driven roles (CEO, prompter, secretary) are excluded, since agent knowledge-sharing is noise in a human's inbox.
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`. Delivery roles (developer / qa / documenter / cell_pm / main_pm) also get `draft_playbook` (draft a curated playbook for the KB). Auditor is restricted to `note` (scope=reflect) + `evidence`, plus the playbook-curation verbs `approve_playbook` / `reject_playbook` / `archive_playbook` (a bounded, deliberate expansion — KB curation, not agent comms, so its no-`say`/no-`dm` restriction holds). 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 `note`/journal write returns as soon as the entry is persisted; RAG indexing (Ollama embedding) runs fire-and-forget, so the tool no longer times out under concurrent load.
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. The verb runner re-checks the task after each composed atomic action and, on a concurrent mid-verb state change, fails fast with a clean `INVALID_STATE` (re-fetch + re-issue) rather than crashing on a `None` dereference.
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`).
**Multi-repo CI-watch (default-off).** The fan-out generalization of self-heal: instead of RoboCo's single own repo, it watches every project the operator opts into (`projects.ci_watch_enabled`, migration 048) and, on a red CI conclusion on that project's default branch, opens one fix task into that project's lifecycle that rides the normal delivery flow (+ PR-review gate) and never auto-merges. It reuses the exact hardened per-project `GitService.get_latest_ci_conclusion` (a missing signal is "unknown", never a false green; per-project errors are isolated and never abort the sweep), and is bounded + deduped per repo by `git_url` (a monorepo's cell-projects share one fix task) with per-cycle / rolling caps. Armed by `ROBOCO_CI_WATCH_ENABLED` (+ `_INTERVAL_SECONDS` / `_MAX_OPEN_TASKS` / `_MAX_PER_CYCLE` / `_DEFAULT_WORKFLOW`) and per-project `ci_watch_enabled` / `ci_watch_workflow`; `MultiProjectCITelemetrySource` (`roboco/services/telemetry/source.py`) + `CiWatchEngine` (`roboco/services/ci_watch_engine.py`) + a dedicated orchestrator `_ci_watch_loop`. The single-repo self-heal loop is untouched.
**Dependency-update bot (default-off).** A per-project engine mirroring the self-heal/CI-watch shape: weekly (default) it probes whether a dependency upgrade would change a project's lockfiles and, if so, opens one "update dependencies" task that rides the normal delivery flow (+ PR-review gate) and never auto-merges. Detection is read-only — `WorkspaceService.dry_upgrade_changes_lockfile` runs the project's `dep_update_command` (e.g. `uv lock --upgrade`) in a throwaway clone of the read clone and diffs the lockfile paths (`dep_update_paths`, or inferred `uv.lock`/`pnpm-lock.yaml`); the read clone is never mutated, nothing is committed/pushed, and a null/failing command originates nothing (fail-safe). A project participates only when `projects.dep_update_command` is set (migration 049); bounded + deduped per `git_url` with per-cycle/rolling caps. Armed by `ROBOCO_DEP_UPDATE_ENABLED` (+ `_INTERVAL_SECONDS` default 604800 / `_MAX_OPEN_TASKS` / `_MAX_PER_CYCLE`); `DepUpdateEngine` (`roboco/services/dep_update_engine.py`) + a dedicated `_dep_update_loop`.
**Gated release manager (default-off).** The autonomy that automates cutting a release up to the decision. A default-off background loop (`ReleaseManagerEngine` + `_release_manager_loop`) runs the deterministic readiness sweep (`ReleaseReadinessService.assess`, `roboco/services/release_readiness.py`) — diff-since-tag → conventional-commit classification → semver bump → version-reference completeness (the missed-ref guard) → CHANGELOG completeness → docs-drift (agent count) → migration single-head → gate state — and, past a threshold (`ROBOCO_RELEASE_MIN_COMMITS`, or any feat/security) with a green gate, originates ONE **release proposal** held for the CEO. The proposal is a `source='release_manager'` task owned by the Secretary, HELD (`confirmed_by_human=False`) and skipped by every dispatcher — acted on only by the CEO-gated routes, never delivered. The CEO approves or rejects-with-changes in the panel (`release-proposal-card.tsx`; `GET/POST /api/release/proposal{,/approve,/reject}`, CEO-only); approval runs the **fail-closed**`ReleaseExecutor` (`roboco/services/release_executor.py`): write the bumps across the canonical set (derived from the previous `chore(release):` commit) + the CHANGELOG entry, run `make quality` (abort before commit on red), commit `chore(release): X.Y.Z` (signed) + push, wait for green release-commit CI (abort before publish on red), then `gh release create vX.Y.Z`. Idempotent (an already-published version is a no-op) and never publishes without the CEO. Correctness is deterministic code, not agent judgment; the only generative step is the CHANGELOG prose, which the CEO reviews. Armed by `ROBOCO_RELEASE_MANAGER_ENABLED` (+ `ROBOCO_RELEASE_MIN_COMMITS` / `_INTERVAL_SECONDS`). Auto-deploy stays out of scope — publishing builds images; deploying to the NAS is the CEO's manual step.
**Organizational memory loop (default-off).** Closes the learn→reuse loop so agents stop cold-respawning blind. Three parts, all gated by `ROBOCO_ORG_MEMORY_ENABLED`: ① **capture** — at task completion `TaskService._completion_learnings_for` distills ONE high-signal lesson (Problem→Approach→Gotcha, ≤120 words) via the local model (`MemoryDistiller`, `roboco/services/memory_distiller.py`) instead of the noisy raw-notes/duration capture (flag-off keeps the legacy capture); journal indexing excludes `is_private` reflections from the shared corpus. ② **retrieve (keystone)** — on claim, `_briefing_for` injects `context_briefing["institutional_memory"]`: top-K (`ROBOCO_ORG_MEMORY_TOP_K`) relevance-floored (`ROBOCO_ORG_MEMORY_MIN_SCORE`) lessons + approved playbooks from a role-shaped query (`EvidenceRepo.similar_memory` over the LEARNINGS + PLAYBOOKS pgvector indexes); below the floor nothing is injected (no briefing bloat). ③ **playbooks** — a first-class curated procedure store: `PlaybookTable` (migration 050), the `PLAYBOOKS` OptimalService index, the `draft_playbook` content verb (delivery roles), Auditor `approve_playbook`/`reject_playbook`/`archive_playbook` curation (approval indexes it), and the panel review queue (`playbook-review-queue.tsx`; `/api/playbooks` Auditor/CEO routes). Distillation runs on the local model only — never a cloud LLM in the hot path; every step is best-effort (a failure never blocks completion or the briefing).
**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`), gateway-health recovery (`ROBOCO_GATEWAY_HEALTH_ENABLED`), multi-repo CI-watch (`ROBOCO_CI_WATCH_ENABLED`), the dependency-update bot (`ROBOCO_DEP_UPDATE_ENABLED`), the gated release manager (`ROBOCO_RELEASE_MANAGER_ENABLED`), the organizational memory loop (`ROBOCO_ORG_MEMORY_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.
**MegaTask** lets the CEO describe several tasks in one Intake chat and ship them as one collision-aware, sequenced batch — even across projects that don't share a codebase (the motivating case: a SaaS app + its OSS core engine + a framework adapter). It is a **core capability, not a feature flag** (additive + opt-in by nature: proposed only when the CEO asks for several tasks; single-task intake is byte-for-byte unchanged), branded "MegaTask" on every user-facing surface while internal names stay technical (`batch_id`, `SequencingService`).
**The umbrella model.** A MegaTask's identity is a real **umbrella** task — branchless, no PR of its own — over N **root-subtasks**, each a real Main-PM coordination root with its own `project_id`, branch, and PR. Hierarchy: Umbrella (Main PM) → N Root-subtasks (Main PM) → Cell tasks (cell PMs) → Dev subtasks. One extra Main-PM layer on top of the normal model. The umbrella is the single board-review / CEO-approve / Main-PM-coordinate unit, so the batch plugs into the existing coordination-root flow for free (task tree, progress rollup, CEO queue).
**Identity predicate (single source of truth).**`roboco/foundation/policy/batch.py`: `is_batch_umbrella` (`batch_id` set AND `parent_task_id` None), `is_batch_root_subtask` (`batch_id` set AND parented), `is_branchless_coordination` ((no-project AND product) OR umbrella). Every git-exemption site consults it so the umbrella's exemptions can't drift: the orchestrator's `_is_coordination_task`, the claim→in_progress branch gate (`GitContext.is_coordination`), `_ensure_branch_for_task` (returns `""` for an umbrella), and the CEO-reject routing. `submit_root` hard-rejects an umbrella (it assembles no PR); umbrella completion reuses the existing branchless path (`all_subtasks_terminal`, PR waived → escalate to CEO).
**Sequencing.** The pure `SequencingService.analyze(surfaces, cell_of, cell_capacity)` (`roboco/services/sequencing.py`; schema in `roboco/foundation/policy/sequencing/`) turns each draft's collision surface — `intends_to_touch` (globs), `adds_migration`, `touches_shared` — into a dependency DAG + Kahn-layered **waves**: file-overlap serializes (more-important first by `(priority, idx)`), migration-adders chain serially, a shared-surface edit runs after each non-shared task it overlaps (file-overlap-conditioned), independent tasks run in parallel; cell-contention only warns. Correctness lives in code, not agent judgment. The columns `tasks.batch_id` + `intends_to_touch` / `adds_migration` / `touches_shared` are migration **046**.
**Intake + create path.** The intake chat can be scoped to a **MegaTask** (a multi-project picker → `StartLiveRequest.project_ids`); the orchestrator clones each repo (`_clone_intake_scope` / `_slugs_for_project_ids`, the multi-repo machinery products already used). The intake agent proposes the whole batch with one **`propose_batch`** tool call — wired on both runtimes (the Claude SDK driver emits one `batch` stream chunk; the grok `intake_server` POSTs a `batch` relay event). The panel's third intake scope accumulates it into a Review-MegaTask card → `POST /prompter/live/{session}/confirm-batch`. `PrompterService.confirm_live_batch` builds the umbrella + N root-subtasks (via `create_task_from_draft` + a `BatchPlacement`) and wires the analyzer edges through `add_dependency`. The Board route holds the root-subtasks in BACKLOG until `approve_and_start` releases them (`_activate_batch_root_subtasks`); the Main-PM route dispatches wave 0 at once. The Product Owner + Head of Marketing review the whole batch (their identity prompts carry a MegaTask section).
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/channels/{id}`, `/ws/agents/{id}`, `/ws/sessions/{id}`, `/ws/notifications/{id}` | Per-resource live streams — `/ws/channels` + `/ws/sessions` carry live `message.new` frames (from `EventType.MESSAGE_SENT`), so a session transcript updates without a manual refresh |
| `/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. `MESSAGE_SENT` is the worked example: `send_message` publishes it, `_handle_message_event` fans it out to `/ws/sessions/{id}` + `/ws/channels/{id}` as a `message.new` frame, and the panel's `useSessionStream` consumes it.
- **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. The same break also catches the **Claude session-limit** 429 (the org's 5-hour usage window): an agent exiting with a 0-token session-limit rejection parks the provider and is auto-revived when the window resets, instead of fleet-wide crash-respawning straight back into the limit. 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.
- **Orchestrator runtime-state durability.** The PM-respawn loop breaker (`_pm_respawn_tracker`, the `(agent_slug, task_id) → strike-count` circuit breaker) is **DB-durable** via the `respawn_tracker` table (migration 051): each gate mutation write-throughs fire-and-forget on the `_bg_tasks` set (`_schedule_respawn_persist` → `_persist_respawn_record`), and `restore_respawn_tracker()` repopulates it at `start()`, validating each row against live tasks (terminal/missing rows are evicted). Kept only in memory it reset to `count=1` on every restart and re-burned the whole strike threshold (4 spawns) against a still-wedged task. It mirrors the `WaitingRecordTable` / `restore_waiting_records` pattern: best-effort (a DB hiccup degrades to in-memory-only — it can only ever *suppress* a spawn, never manufacture one) and inert when the table is empty. The companion `_instances` registry is **reconciled-from-Docker** (not persisted) at startup via `_readopt_running_agents`, so the reaper's liveness path and the spawn gate's `_is_agent_active` check see surviving containers immediately after a restart.
- **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.