How do I install the Data skill?

Run npx skillmds@latest add persimmon-automation-labs/data in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Data skill do?

Data — Index It is listed under Coding & Dev Tools on SkillMD.

This skill has not completed SkillMD's automated safety review yet. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Data?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Persimmon-Automation-Labs (@persimmon-automation-labs) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Data by persimmon-automation-labs — Agent Skill

Name: Data
Rating: 4.2 (5 reviews)
Author: Persimmon-Automation-Labs

File contents

Data — Index

Persimmon data = PostgreSQL with pgvector, accessed through Prisma with one shared client. This mother is a map; follow the child for the actual work.

Trigger

"Design the schema for…" / "Add a Prisma model / migration"
"Store embeddings" / "vector column" / "pgvector"
"Search by similarity" / "HNSW index"

The child skills

Skill	When to use	Owns
`data-prisma-pgvector`	Any schema design, migration, vector column, or similarity query	Prisma schema patterns, pgvector extension setup, HNSW indexing (`vector_cosine_ops`), cosine-similarity queries, the one-shared-client rule
`data-schema-design`	Modeling rigor before a schema is final	Snapshot-mutable-values, lifecycle enums, join models, FK/cardinality, the validation lenses
`data-booking-availability`	Reservations / slots / availability	Slot schema, availability queries, blackout/lead-time, waitlist, deposits
`data-db-cli`	Inspect or query the live DB without writing a script	The read-only-by-default `db` CLI (`npm run db`) + Postgres MCP setup, the `--write`/`--prod` safety gates

Persimmon data defaults — one-screen summary

One Prisma client in src/lib/db.ts. Never instantiate PrismaClient elsewhere.
Migrations: prisma migrate dev locally. On Railway, apply via prisma db push in the build step OR a migrate-deploy job — pick one per project and stick with it.
After db push with enum/model changes: restart the dev server (the running Prisma client is stale).
pgvector index: HNSW beats IVFFlat for recall + latency under ~10M rows. Build with CREATE INDEX ... USING hnsw (embedding vector_cosine_ops).
Never query a filtered-subset HNSW index without the filter.
Naming: models PascalCase singular; fields camelCase; createdAt/updatedAt on every model; Postgres enums, not string constants.

Anti-patterns banned

Instantiating PrismaClient outside src/lib/db.ts
Mixing migrate and db push strategies in one project
Unfiltered queries against a filtered-subset vector index
String constants where a Postgres enum belongs

Relationship to other mothers

Mother	Connection
`ai`	`ai-rag-retrieval` stores/searches embeddings here
`stack`	Server Actions read/write through the shared Prisma client
`quality`	N+1, unbounded lists, missing indexes flagged by `quality-review-data-layer`

---name: datadescription: Data — Index---# Data — IndexPersimmon data = PostgreSQL with `pgvector`, accessed through Prisma with one shared client. This mother is a map; follow the child for the actual work.## Trigger- "Design the schema for…" / "Add a Prisma model / migration"- "Store embeddings" / "vector column" / "pgvector"- "Search by similarity" / "HNSW index"## The child skills| Skill | When to use | Owns ||---|---|---|| `data-prisma-pgvector` | Any schema design, migration, vector column, or similarity query | Prisma schema patterns, pgvector extension setup, HNSW indexing (`vector_cosine_ops`), cosine-similarity queries, the one-shared-client rule || `data-schema-design` | Modeling rigor before a schema is final | Snapshot-mutable-values, lifecycle enums, join models, FK/cardinality, the validation lenses || `data-booking-availability` | Reservations / slots / availability | Slot schema, availability queries, blackout/lead-time, waitlist, deposits || `data-db-cli` | Inspect or query the live DB without writing a script | The read-only-by-default `db` CLI (`npm run db`) + Postgres MCP setup, the `--write`/`--prod` safety gates |## Persimmon data defaults — one-screen summary- **One Prisma client** in `src/lib/db.ts`. Never instantiate `PrismaClient` elsewhere.- **Migrations**: `prisma migrate dev` locally. On Railway, apply via `prisma db push` in the build step OR a migrate-deploy job — pick one per project and stick with it.- **After `db push` with enum/model changes**: restart the dev server (the running Prisma client is stale).- **pgvector index**: HNSW beats IVFFlat for recall + latency under ~10M rows. Build with `CREATE INDEX ... USING hnsw (embedding vector_cosine_ops)`.- **Never query a filtered-subset HNSW index without the filter.**- **Naming**: models `PascalCase` singular; fields `camelCase`; `createdAt`/`updatedAt` on every model; Postgres enums, not string constants.## Anti-patterns banned- Instantiating `PrismaClient` outside `src/lib/db.ts`- Mixing `migrate` and `db push` strategies in one project- Unfiltered queries against a filtered-subset vector index- String constants where a Postgres enum belongs## Relationship to other mothers| Mother | Connection ||---|---|| `ai` | `ai-rag-retrieval` stores/searches embeddings here || `stack` | Server Actions read/write through the shared Prisma client || `quality` | N+1, unbounded lists, missing indexes flagged by `quality-review-data-layer` |

Frequently asked questions

Data