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Generate realistic, screenshot-ready seed data for MemOS — a believable org with teams, projects, agents, OKRs, briefs, and a rich graph of facts/learnings/artifacts. Use before demos, screenshots, or recording the README Loom.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
| name | demo-seed |
| description | Generate realistic, screenshot-ready seed data for MemOS — a believable org with teams, projects, agents, OKRs, briefs, and a rich graph of facts/learnings/artifacts. Use before demos, screenshots, or recording the README Loom. |
A portfolio project lives or dies on the demo. Empty tables screenshot badly. This skill populates a believable, dense, internally-consistent dataset so the dashboard looks alive and the provenance graph has depth.
packages/api/src/db/seed.ts (idempotent, run via pnpm db:seed)Seed ONE believable org so everything connects:
team.ml-platform, team.growth).project.rag-search, project.onboarding-funnel, project.cost-optimization). Mark one okrs_required=true.trust_score (0.62 → 0.98) and last_checkin_at spread across the last week. Include one low-trust agent (for the leaderboard contrast) and one platform "critic" agent.status (some achieved, some pending), realistic metric_current vs metric_target so rollup bars show partial progress. Use varied units (percent, cents per piece, seconds, USD) and both directions (up/down).status (mostly complete, a couple open, one failed).applies_to uses problem-domain tags only.choices (one closed with outcome, one open/stale for the loop-close critic to flag).now()), so the activity feed has a believable timeline.reuse_count and reuse_success_count (the "compounding capital" story).≤, a —, and an emoji somewhere to prove encoding is clean.Truncate-then-insert, or upsert by stable IDs, so re-running pnpm db:seed is safe.
pnpm db:seed runs clean, the dashboard's OKR tree / activity feed / provenance graph / trust leaderboard all look full and believable, and there's at least one deep provenance chain worth screenshotting.
Write a correct Drizzle schema change plus migration and Row-Level Security policy for MemOS. Use when adding or altering any table, index, or RLS policy.
Run an HLD + LLD design review on a proposed plan BEFORE coding a non-trivial MemOS feature. Use at the start of any feature that touches more than one module, the data model, or a core invariant.
Audit that the MemOS core write-gating invariants (evidence gate, non-obvious gate, provenance thread, tenant isolation) are actually enforced and tested. Run before merging any change to the fact/learning/artifact/workflow write path.
Build a polished MemOS dashboard component to the project design system (Next.js App Router, Tailwind, shadcn/ui, Framer Motion). Use for any new UI piece — OKR tree, activity feed, provenance graph, brief authoring, etc.
Add a new MemOS API intent end-to-end (Zod schema, handler, route registration, test, and API docs) in the consistent project pattern. Use whenever adding or modifying an intent like fact.record, workflow.create, brief.fetch.
Capture an Architecture Decision Record for a real design choice in MemOS. Use whenever a non-trivial decision is made (tech choice, schema modeling, isolation strategy, a tradeoff with alternatives).