data-model

Data Model

Instructions

Create or update docs/data_model.md based on docs/requirements.md and docs/vision.md. Produce an optional Mermaid ER diagram followed by an attribute table for each entity.

DO NOT

• Use PlantUML
• Skip the attribute table for any entity that has more than a primary key
• Invent entities not derivable from requirements
• Hard-code pgvector columns unless a FR mentions search, similarity, or RAG

Output Format

# Data Model

## Entity Relationship Diagram

```mermaid
erDiagram
    USER {
        int id PK
        string email
        string name
    }
    POST {
        int id PK
        string title
        int user_id FK
    }
    USER ||--o{ POST : "writes"

Entities

User

Attribute	Type	Constraints	Description
id	integer	PK, auto	Primary key
email	varchar(255)	NOT NULL, UNIQUE	Login identifier
name	varchar(255)	NOT NULL	Display name
created_at	timestamp	NOT NULL, DEFAULT now()	Creation time

Post

Attribute	Type	Constraints	Description
id	integer	PK, auto	Primary key
title	varchar(500)	NOT NULL	Post title
body	text	NOT NULL	Content
user_id	integer	FK → User.id	Author
embedding	vector(1536)	nullable	Semantic embedding for search
created_at	timestamp	NOT NULL, DEFAULT now()	Creation time

## pgvector notes

Add a `vector(1536)` column (and note "requires pgvector extension") to any entity whose
features mention: semantic search, similarity search, RAG, embeddings, recommendations, or "find similar".

## Workflow

1. Read `docs/requirements.md` to identify entities from FR user stories
2. Read `docs/vision.md` for domain context
3. Infer relationships (one-to-many, many-to-many) from requirements
4. Draw Mermaid ER diagram (skip if < 2 entities)
5. Write attribute table for each entity
6. Mark any vector columns needed for search features
7. Write `docs/data_model.md`
8. Suggest next step: `/feature-spec`