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>
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>
