The Multi-Agent Workbench shipped end-to-end (commits1771063dfthrough7c89eb625). This commit turns the plan doc into a proper history + post- mortem and captures the deferred Team-Workbench as its own forward plan so the architectural breadcrumbs don't rot. docs/plans/multi-agent-workbench.md: - Status bumped to ✅ Shipped; every phase checkbox flipped. - Open-questions section rewritten with the decisions that were actually made (name-unique via store write-time check, per-source system principalIds, policy fully migrated, scene binding default- empty with smart suggestion). - New "Shipping-Historie" table mapping each phase to its commit, the number of files touched, and the test outcome. - New "Lessons Learnt + Follow-Up Ideen" with: * What went better than expected (L3 Actor cutover, getOrCreate instead of unique index, displayName caching) * Thin spots worth revisiting (avatar not on Actor, missing token counter for budget, no missions list on agent detail, no drag-reassign, scene binding doesn't drive filters yet) * Five deferred follow-up projects (team features, agent memory self-update, agent-to-agent messaging, meta-planner, per-agent encryption domains) docs/plans/team-workbench.md (NEW): - Full forward-looking plan for the deferred Team-Workbench. - Two use-cases (human multi-user vs multi-agent sharing team context) with the observation that they share the same infra. - Decision candidates table (still open — meant as T0 RFC fodder, not baked in). - Architecture sketch with data-model deltas over the current single-user shape. - Encryption subsection dedicated to the hardest problems: team-key wrapping per member (reuses Mission-Grant pattern), member-removal rotation (lazy vs eager), Zero-Knowledge-mode incompatibility. - T0..T6 phasing (~7 weeks for a clean first-pass). - Section "Wie Multi-Agent dafür den Weg geebnet hat" enumerating the four invariants the shipped Phase 0-7 deliberately preserved to make this plan cheap when it lands. docs/plans/README.md (NEW): - Index doc with the AI/Workbench roadmap as an ASCII flow so future contributors can locate themselves in the sequence without reading three 400-line plans first. docs/future/AI_AGENTS_IDEAS.md: - Header marks Point 1 (encrypted tables) as shipped via the Mission Grant plan; points 2-8 stay relevant. Cross-link to all three plan docs so this stays the go-to backlog. services/mana-ai/CLAUDE.md: - Design-context header expanded to link to all four related docs (arch §20-22, both shipped plans, forward team plan, ideas backlog). No code changes. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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mana-ai
Background runner for the AI Workbench. Picks up due Missions from the mana_sync Postgres and plans/proposes next steps without requiring an open browser tab. Complements the foreground startMissionTick in the webapp (apps/mana/apps/web/src/lib/data/ai/missions/setup.ts).
Design context:
docs/architecture/COMPANION_BRAIN_ARCHITECTURE.md§20 (AI Workbench base), §21 (Mission Key-Grants), §22 (Multi-Agent Workbench)docs/plans/ai-mission-key-grant.md— Shipped (per-mission key-grant for encrypted inputs)docs/plans/multi-agent-workbench.md— Shipped (named agents, per-agent policy/memory, scene lens)docs/plans/team-workbench.md— Forward-looking (multi-user + shared team context)docs/future/AI_AGENTS_IDEAS.md— Unshipped improvement backlog
Status: v0.3 (full close-the-loop)
What works end-to-end:
- Boots as a Hono/Bun service on port
3067 - Exposes
/healthand service-key-gated/internal/tick - Replays
sync_changesforappId='ai' / table='aiMissions'into live Mission records via field-level LWW (src/db/missions-projection.ts) - Lists due missions (
state='active' && nextRunAt <= now()) - For each due mission: shared
buildPlannerPrompt(from@mana/shared-ai) → mana-llm/v1/chat/completions→ strictparsePlannerResponse - Per-mission try/catch so one flaky LLM response doesn't abort the queue; stats differentiate
plansProduced/plansWrittenBack/parseFailures - Server-side tool allow-list (
src/planner/tools.ts) mirrors the webapp'sDEFAULT_AI_POLICYproposesubset - Write-back:
db/iteration-writer.tsappends the server-produced iteration toMission.iterations[]via async_changesINSERT under an RLS-scopedwithUsertransaction. Row is attributed with actor{kind:'system', source:'mission-runner'}. - Webapp staging effect (
server-iteration-staging.ts) picks up the synced iteration and translates each PlanStep into a local Proposal with full AI-actor attribution (missionId + iterationId + rationale). Idempotent via durableproposalIdmarkers. - Server-side input resolvers for plaintext tables —
db/resolvers/with a pluggable registry + single-record LWW replay (record-replay.ts).goalsresolver ships by default. Encrypted tables (notes, kontext, tasks, events, journal, …) are intentionally not resolved server-side; those missions depend on the foreground runner which decrypts client-side. Seeresolvers/types.tsfor the privacy rationale. - Materialized mission snapshots —
mana_ai.mission_snapshotstable with per-tick incremental refresh (db/snapshot-refresh.ts).listDueMissionsis now a single indexed SELECT; the prior O(N changes) LWW replay stays only inmergeAndFilterfor tests. Idempotentmigrate()on boot creates the schema. - Prometheus metrics on
/metrics— process defaults withmana_ai_prefix + counters (mana_ai_ticks_total,mana_ai_plans_produced_total,mana_ai_plans_written_back_total,mana_ai_parse_failures_total,mana_ai_mission_errors_total,mana_ai_snapshots_*) and histograms (mana_ai_tick_duration_seconds,mana_ai_planner_request_duration_seconds,mana_ai_http_request_duration_seconds). Scraped 30s bydocker/prometheus/prometheus.yml'smana-aijob./healthis also blackbox-probed and surfaces on status.mana.how under "Internal" as "Mana AI Runner".
All v0.3 roadmap items shipped. Future polish (not blockers):
- Multi-instance deploy with advisory locks on snapshot refresh (today single-process)
- Read-only
/internal/missions/:userIdendpoint for ops inspection
Status: v0.4 (Mission Key-Grants, in Arbeit)
Opt-in Mechanismus zum Entschluesseln der encrypted Input-Tabellen (notes, tasks, events, journal, kontext) serverseitig. Plan: docs/plans/ai-mission-key-grant.md. Architektur: docs/architecture/COMPANION_BRAIN_ARCHITECTURE.md §21.
Was steht (Phase 0-2, Backend):
- RSA-OAEP-2048 keypair slots —
MANA_AI_PRIVATE_KEY_PEM(ai) /MANA_AI_PUBLIC_KEY_PEM(auth). Ohne Env-Var laeuft der Service unveraendert; Grants werden dann einfach uebersprungen. - Canonical HKDF in
@mana/shared-ai(missions/grant.ts). Scope-Binding (tables + recordIds) viainfo-String → Scope-Change = neuer Key = existierender Grant automatisch invalidiert. POST /api/v1/me/ai-mission-grantauf mana-auth — leitet MDK ab, RSA-wrapped, lehnt Zero-Knowledge-User ab, TTL-clamped [1h, 30d].mana_ai.decrypt_auditTabelle + RLS (user_scopeviaapp.current_user_id). Append-only.crypto/unwrap-grant.ts— Private-Key-Import, Grant-Entwrapping mit structured reasons (not-configured/expired/wrap-rejected/malformed).crypto/decrypt-value.ts— Mirror des webapp AES-GCM wire format (enc:1:<iv>.<ct>).- Encrypted Resolver (
db/resolvers/encrypted.ts) fuer notes / tasks / calendar / journal / kontext. Checkt recordId-Allowlist, replayt Record, entschluesseltenc:1:-Felder, schreibt Audit-Row pro Record. - Tick-Loop-Integration (
cron/tick.ts) — unwrappt Grant pro Mission, bautResolverContextmitmdk + allowlist, Key lebt nur waehrendplanOneMission. - Metriken:
mana_ai_decrypts_total{table},mana_ai_grant_scope_violations_total{table}(Alert > 0!),mana_ai_grant_skips_total{reason}.
Was offen ist (Phase 3, Frontend):
- Webapp
MissionGrantDialog+ Consent-Flow im Mission-Detail. - Revoke-Button + "Datenzugriff" Audit-Tab im Workbench.
GET /api/v1/me/ai-auditJWT-gated Endpoint live.- Feature-Flag
PUBLIC_AI_MISSION_GRANTS+ Cloudflare-Tunnel. - Produktions-Keypair auf Mac-Mini unter
secrets/mana-ai/.
Status: v0.5 (Multi-Agent Workbench)
Der Runner wird agent-bewusst — Missionen gehoeren einem benannten Agent, Policy und Memory leben auf dem Agent, Concurrency + Budget werden pro Agent respektiert.
mana_ai.agent_snapshotsTabelle (LWW-Projektion vonagentsaussync_changes).refreshAgentSnapshots+loadActiveAgentsparallel zum Mission-Snapshot-Refresh.ServerMission.agentId+ServerAgent.policydurchgereicht.- Tick resolvt pro Mission den Agent, gated
archived/paused/concurrency, schreibt iteration untermakeAgentActor(agent)Identitaet. <agent_context>Prompt-Block mit plaintextrole+systemPrompt+memory(ciphertext wird uebersprungen).filterToolsByAgentPolicyschneidetdeny-Tools raus bevor der Planner sie sieht.- Metrik
mana_ai_agent_decisions_total{decision}.
Port: 3067
Tech Stack
| Layer | Technology |
|---|---|
| Runtime | Bun |
| Framework | Hono |
| Database | PostgreSQL via postgres driver (read-only against mana_sync) |
| Auth | Service-to-service key; no end-user JWTs |
Quick Start
# Requires mana_sync DB reachable
cd services/mana-ai
bun run dev
# Smoke test
curl http://localhost:3067/health
curl -X POST -H "X-Service-Key: dev-service-key" http://localhost:3067/internal/tick
Environment Variables
PORT=3067
SYNC_DATABASE_URL=postgresql://mana:devpassword@localhost:5432/mana_sync
MANA_LLM_URL=http://localhost:3020
MANA_SERVICE_KEY=dev-service-key
TICK_INTERVAL_MS=60000
TICK_ENABLED=true # flip to false to boot HTTP-only (for Docker health-check)
Architecture
┌────────────────────┐
│ mana-ai (Bun) │
│ :3067 │
│ │ 60s interval
│ ┌─────────────┐ │────────────────┐
│ │ tick loop │ │ │
│ │ runTickOnce │ │ │
│ └─────────────┘ │ │
│ │ │ │
│ │ SELECT │ │
│ ▼ │ │
│ ┌─────────────┐ │ │
│ │ missions- │ │ │
│ │ projection │ │ │
│ │ (LWW replay)│ │ │
│ └─────────────┘ │ ▼
│ │ ┌──────────────┐
│ ┌─────────────┐ │ │ mana_sync │
│ │ planner │───┼─────────▶│ (Postgres) │
│ │ client │ │ └──────────────┘
│ └─────────────┘ │
│ │ │
└───────┼────────────┘
│ POST /v1/chat/completions
▼
┌────────────────────┐
│ mana-llm (Python) │
│ :3020 │
└────────────────────┘
Open design questions (for next PR)
1. How do plan results get back to the user's device?
Proposals live in a local-only Dexie table (pendingProposals) — they don't sync. So the server can't just write proposals directly.
Options:
(a) Write iteration + plan to aiMissions, let the browser stage proposals on arrival.
Server appends an iteration with overallStatus: 'server-planned' and the plan steps. When the webapp next syncs, an effect subscribed to iteration changes translates each step into a local Proposal using the existing createProposal(). Clean: preserves the "proposals are local" invariant. Risk: duplicate proposals if multiple devices pick up the same iteration.
(b) Introduce aiProposedSteps as a synced table.
Server writes here directly; the webapp treats it as a source for its local pendingProposals. Requires a migration step + duplicates the proposal model.
(c) Make pendingProposals sync.
Simplest schema change, most invasive: approvals + rejections now race across devices. Would need server-authoritative state transitions.
Leaning (a) — minimal schema change, single source of truth. Implementation sketch: add iteration.source: 'browser' | 'server' and a "staging queue" on the webapp that dedups via iterationId.
2. Does the server need full LWW replay?
The projection replays every sync_changes row for aiMissions on every tick. For a small user base this is fine; past ~100 users × hundreds of rows it becomes wasteful.
Option: materialized view refreshed on sync-change insert via a trigger or a per-user ai_mission_snapshot table the service maintains. Defer until the load shows up.
3. Planner prompt: duplicate or share?
prompt.ts + parser.ts live in the webapp's @mana/web/src/lib/data/ai/missions/planner/. Server-side copies would drift. Options:
- Extract a
@mana/shared-aipackage with the prompt/parser - Keep two copies with a contract test
- Only the webapp plans; server just triggers the browser via push
First is cleanest; TS source, imports cleanly in both Bun and Vite.
Writing code in here
- No database schema of its own — this service is pure consumer. If you need persistent state (retry queues, per-user cursors), add a separate table namespace under
mana_ai.*schema on themana_syncdatabase, not a new DB. src/db/missions-projection.tsis the ONLY place that does LWW replay. Don't duplicate the logic; add new projection helpers there.- Follow the foreground-runner contract: injected deps (planner, write-back) for tests. Bun's
bun testruns insrc/**/*.test.ts.
Files
services/mana-ai/
├── src/
│ ├── index.ts — Hono bootstrap + tick scheduler wiring
│ ├── config.ts — Env loading
│ ├── cron/tick.ts — Scan loop, overlap-guarded
│ ├── db/
│ │ ├── connection.ts — postgres.js pool
│ │ └── missions-projection.ts — sync_changes → Mission LWW replay
│ ├── planner/client.ts — mana-llm HTTP client (OpenAI-compatible)
│ └── middleware/service-auth.ts — X-Service-Key gate for /internal/*
├── Dockerfile
├── package.json
├── tsconfig.json
└── CLAUDE.md