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3 commits

Author SHA1 Message Date
Till JS
1771063df4 refactor(actor): identity-aware Actor for Multi-Agent Workbench (Phase 1)
Foundation for the Multi-Agent Workbench roadmap
(docs/plans/multi-agent-workbench.md). Every event, record, and
sync_changes row now carries a principal identity + cached display
name in addition to the three-kind discriminator.

Shape change (source of truth in @mana/shared-ai):
  Before: { kind: 'user' | 'ai' | 'system', ...kind-specific fields }
  After:  discriminated union on kind, with
            - common:  principalId, displayName
            - 'user':  principalId = userId
            - 'ai':    principalId = agentId + missionId/iterationId/rationale
            - 'system': principalId = one of SYSTEM_* sentinel strings
                        ('system:projection', 'system:mission-runner', etc.)

Key design calls (from the plan's Q&A):
- System sub-sources get distinct principalIds (not a shared 'system'
  bucket) — lets Workbench filter + revert distinguish projection
  writes from migration writes from server-iteration writes
- displayName cached on the record so renaming an agent doesn't
  rewrite history
- normalizeActor() compat shim fills principalId/displayName on
  legacy rows with 'legacy:*' sentinels so historical events never
  crash the timeline

New exports:
- BaseActor / UserActor / AiActor / SystemActor (narrowed types)
- makeUserActor, makeAgentActor, makeSystemActor (factories with
  typed return)
- SYSTEM_PROJECTION, SYSTEM_RULE, SYSTEM_MIGRATION, SYSTEM_STREAM,
  SYSTEM_MISSION_RUNNER (principalId constants)
- LEGACY_USER_PRINCIPAL, LEGACY_AI_PRINCIPAL, LEGACY_SYSTEM_PRINCIPAL
- isUserActor / isFromMissionRunner predicates

Webapp:
- data/events/actor.ts now re-exports from shared-ai, keeps runtime
  ambient-context (runAs, getCurrentActor) local
- bindDefaultUser(userId, displayName) lets the auth layer replace
  the legacy placeholder with the real logged-in user actor at login
- Mission runner + server-iteration-staging stamp LEGACY_AI_PRINCIPAL
  as the agentId placeholder — Phase 2 will thread the real agent
- Streaks projection uses makeSystemActor(SYSTEM_PROJECTION)
- All test fixtures migrated to factories

Service:
- mana-ai/db/iteration-writer.ts stamps makeSystemActor(
  SYSTEM_MISSION_RUNNER) instead of the old { kind:'system',
  source:'mission-runner' } shape. Phase 3 will switch this to an
  agent actor per mission.

Tests: 26 shared-ai + 21 webapp vitest + 35 mana-ai — all green.
svelte-check: 0 errors, 0 warnings.

No behavior change; purely a type + shape upgrade. Old sync_changes
rows parse via the normalizeActor compat shim at read time.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-15 20:13:57 +02:00
Till JS
5e01763caa feat(ai): close the loop — server write-back + webapp staging effect
Completes the off-tab AI pipeline. mana-ai now writes produced plans
back to `sync_changes` as a server-sourced Mission iteration; the webapp
picks it up on next sync and translates each PlanStep into a local
Proposal via the existing createProposal flow. User sees the resulting
ghost cards in the matching module's AiProposalInbox with full mission
attribution.

Server (mana-ai v0.3):
- `db/connection.ts` — `withUser(sql, userId, fn)` RLS-scoped tx helper
  mirroring the Go `withUser` pattern (SET LOCAL app.current_user_id)
- `db/iteration-writer.ts`
  - `planToIteration(plan, id, now)` — shared-ai AiPlanOutput → inline
    MissionIteration with `source: 'server'` + status='awaiting-review'
  - `appendServerIteration(sql, input)` — INSERT sync_changes row with
    op=update, data={iterations: [...]} + field_timestamps + actor
    JSONB={kind:'system', source:'mission-runner'}
- `cron/tick.ts` — after parse success: build iteration, append to
  mission.iterations, persist via appendServerIteration. Stats now
  include `plansWrittenBack`.

Actor union:
- `packages/shared-ai/src/actor.ts` + webapp actor: `system.source` gains
  `'mission-runner'` so the server's own writes are attributed correctly
  and distinguishable from projection/rule writes

Webapp:
- `data/ai/missions/server-iteration-staging.ts`
  - `startServerIterationStaging()` subscribes to aiMissions via Dexie
    liveQuery; on each Mission update, walks iterations looking for
    `source='server'` entries that haven't been staged yet
  - For each such iteration: creates a Proposal per PlanStep under
    `{kind:'ai', missionId, iterationId, rationale}` so policy + hooks
    fire correctly
  - Writes proposalIds back into plan[].proposalId + status='staged' so
    other tabs and app restarts skip re-staging
  - Idempotent: in-memory `processedIterations` Set + durable
    proposalId marker
- Wired into (app)/+layout.svelte alongside startMissionTick
- 3 unit tests: translate server iteration → proposal, skip
  already-staged, ignore browser iterations

Full pipeline now: user creates Mission in /companion/missions →
mana-ai tick picks it up → calls mana-llm → parses plan →
writes iteration → synced to webapp → staging effect creates
proposals → user approves in /todo (or any module) → task lands with
`{actor: ai, missionId, iterationId, rationale}` attribution.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-15 00:29:30 +02:00
Till JS
0d90b12d1c feat(shared-ai): extract planner + mission types to @mana/shared-ai
Single source of truth for AI Workbench types shared between the webapp
(Vite/SvelteKit) and the server-side mana-ai Bun service. Prevents the
two runtimes from drifting on prompt shape or mission structure.

- `@mana/shared-ai` package:
  - `actor.ts` — Actor union (user | ai | system) + helpers, mirrors the
    webapp's runtime type so server-side consumers parse incoming actors
    without re-declaring
  - `missions/types.ts` — Mission, MissionCadence, MissionInputRef,
    MissionIteration, PlanStep, MissionState. Adds optional
    `iteration.source: 'browser' | 'server'` to distinguish foreground
    vs server-produced iterations (groundwork for proposal write-back)
  - `planner/prompt.ts` — `buildPlannerPrompt` pure function
  - `planner/parser.ts` — `parsePlannerResponse` strict JSON validator
  - Vitest smoke tests (2) cover prompt → parse round-trip + unknown-
    tool rejection
- Webapp:
  - `missions/types.ts` re-exports from shared-ai, keeps webapp-local
    `MISSIONS_TABLE` constant + `planStepStatusFromProposal` bridge
  - `missions/planner/{types,prompt,parser}.ts` become re-export stubs
    so existing imports keep working unchanged
  - Existing webapp tests (60) continue to pass — the wire code didn't
    move, just its home

Next: mana-ai service imports buildPlannerPrompt/parsePlannerResponse
from shared-ai + wires mana-llm + writes iteration back as a
'source=server' row (tracked in services/mana-ai/CLAUDE.md).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-15 00:01:57 +02:00