Paths: File paths (shared/, references/, ../ln-*) are relative to skills repo root. If not found at CWD, locate this SKILL.md directory and go up one level for repo root. If shared/ is missing, fetch files via WebFetch from https://raw.githubusercontent.com/levnikolaevich/claude-code-skills/master/skills/{path}.
ln-723-seed-data-generator
Type: L3 Worker Category: 7XX Project Bootstrap
Universal seed data generator with two modes: MIGRATE (parse existing ORM schemas) or GENERATE (create from entity definitions). Outputs to any target format (C#, TypeScript, Python, JSON, SQL).
Purpose & Scope
| Aspect | Description |
|---|
| Input | ORM schema files (MIGRATE) or entity list (GENERATE) |
| Output | Seed data files in target format |
| Modes | MIGRATE: parse existing ORM → seed data. GENERATE: entity definitions → seed data |
Scope boundaries:
- Parses ORM schema definitions or accepts entity lists
- Generates seed data in requested target format
- Creates realistic sample data using faker libraries
- Does not generate database migrations, EF Core configs, or ORM models
Mode Selection
| Mode | When | Input | Source |
|---|
| MIGRATE | TRANSFORM pipeline — existing ORM schemas found | ORM schema files | Drizzle, Prisma, TypeORM, EF Core, SQLAlchemy, Django ORM |
| GENERATE | CREATE pipeline — no existing schemas | Entity list from ln-700 Phase 0 | User-provided or starter template (User, Role) |
If GENERATE mode receives no entity list, generate starter template with User (id, name, email, role, createdAt) and Role (id, name, description).
Target Formats
| Format | Output File | Faker Library | Use Case |
|---|
| C# MockData | MockData.cs | Bogus | .NET projects |
| TypeScript fixtures | seed.ts | Faker.js | Node/React projects |
| Python factories | factories.py | Faker (Python) | Django/Flask projects |
| JSON | seed.json | — | API testing, import scripts |
| SQL | seed.sql | — | Direct DB seeding |
Workflow
| Phase | Name | Actions | Output |
|---|
| 1 | Parse/Define | 1A: Parse ORM schema (MIGRATE) or 1B: Accept entity list (GENERATE) | Entity model |
| 2 | Map Types | Apply universal type mapping to target format | Target type definitions |
| 3 | Generate Seed Data | Create seed files with faker-based realistic data | Seed data files |
| 4 | Verify | Validate relationships, check syntax | Valid seed files |
Phase 1: Parse/Define
1A: MIGRATE Mode — Parse ORM Schema
| Step | Action | Reference |
|---|
| 1A.1 | Locate schema file(s) | — |
| 1A.2 | Auto-detect ORM type | orm_patterns.md — ORM Auto-Detection table |
| 1A.3 | Extract table/model definitions | orm_patterns.md — per-ORM parsing section |
| 1A.4 | Extract column definitions with types | orm_patterns.md |
| 1A.5 | Identify constraints (PK, FK, nullable, unique) | orm_patterns.md |
| 1A.6 | Extract enum definitions | orm_patterns.md |
1B: GENERATE Mode — Accept Entity Definitions
| Step | Action | Reference |
|---|
| 1B.1 | Receive entity list from orchestrator (or use starter template) | — |
| 1B.2 | Parse entity definitions (name, fields, types) | — |
| 1B.3 | Infer relationships from field names (userId → FK to User) | relationship_mapping.md |
| 1B.4 | Apply default constraints (id = PK, *Id = FK) | — |
Output: Entity model with columns, types, and constraints.
Phase 2: Map Types
Convert entity types to target format types.
| Step | Action | Reference |
|---|
| 2.1 | Select target format (from orchestrator params) | — |
| 2.2 | Map column types to target format | type_mapping.md — Universal Type Mapping table |
| 2.3 | Determine nullable status per target | type_mapping.md |
| 2.4 | Map foreign keys and relationships | relationship_mapping.md |
| 2.5 | Transform names to target convention | See Name Conventions table below |
Name Conventions by Target:
| Target | Class/Model | Property/Field | File |
|---|
| C# | PascalCase singular | PascalCase | PascalCase.cs |
| TypeScript | PascalCase singular | camelCase | camelCase.ts |
| Python | PascalCase singular | snake_case | snake_case.py |
| JSON | camelCase | camelCase | kebab-case.json |
| SQL | snake_case plural | snake_case | snake_case.sql |
Phase 3: Generate Seed Data
Create seed files with realistic data using faker libraries.
| Step | Action | Reference |
|---|
| 3.1 | Determine generation order (parents → children) | relationship_mapping.md |
| 3.2 | Generate IDs (GUIDs/UUIDs) for all entities | data_generation.md |
| 3.3 | Generate field values using faker | data_generation.md, type_mapping.md — Faker Integration |
| 3.4 | Ensure FK relationships valid (child references existing parent ID) | relationship_mapping.md |
| 3.5 | Write seed file in target format | — |
Faker integration rule: All generated seed files MUST use faker libraries for realistic data with deterministic seeding (fixed seed value for reproducibility).
| Target | Faker Setup |
|---|
| C# | var faker = new Bogus.Faker(); Randomizer.Seed = new Random(42); |
| TypeScript | import {faker} from '@faker-js/faker'; faker.seed(42); |
| Python | from faker import Faker; fake = Faker(); Faker.seed(42) |
Generation order by dependency:
| Order | Entity Type | Generate After |
|---|
| 1 | Root entities (no FK) | First |
| 2 | First-level children | Parents exist |
| 3 | Second-level children | Grandparents exist |
| N | Deepest children | All ancestors exist |
Phase 4: Verify
| Check | Method | Expected |
|---|
| Syntax valid | Language-specific check | No syntax errors |
| FKs valid | Cross-reference | All FKs point to existing IDs |
| Types correct | Type analysis | Proper types for target format |
| Names follow convention | Pattern check | Per-target naming convention |
| Faker deterministic | Re-run with same seed | Identical output |
Supported ORM Detection
| ORM | Detection Pattern | Ecosystem |
|---|
| Drizzle | pgTable(), mysqlTable(), sqliteTable() | Node.js |
| Prisma | model X { syntax in .prisma files | Node.js |
| TypeORM | @Entity(), @Column() decorators | Node.js |
| EF Core | DbContext, DbSet<>, [Table] attributes | .NET |
| SQLAlchemy | Base = declarative_base(), Column() | Python |
| Django ORM | models.Model, models.CharField() | Python |
Entity Transformation Rules
| Source | Target | Transformation |
|---|
| Table name (plural, snake) | Class name (singular, Pascal) | user_profiles → UserProfile |
| Column name (snake) | Property name (target convention) | created_at → CreatedAt / createdAt / created_at |
| Enum name | Enum type (Pascal) | status_enum → StatusEnum |
| FK column | Navigation property | user_id → UserId / userId |
Sample Data Guidelines
| Field Type | Sample Count | Distribution |
|---|
| Root entities | 3-5 items | Varied status/priority |
| Child entities | 5-10 items | Distributed across parents |
| Leaf entities | 10-20 items | Realistic variety |
Critical Rules
- Single Responsibility: Generate only seed data, no ORM models or migrations
- Idempotent: Can re-run with same seed to produce identical output
- Valid Relationships: All FKs must reference existing parent IDs
- Faker Required: Use faker libraries for realistic data, never random strings
- Deterministic Seeding: Fixed seed value (42) for reproducibility across re-runs
- Generation Order: Parents before children, always
- Mode Awareness: MIGRATE parses files; GENERATE accepts definitions — never mix
Definition of Done
- Mode determined (MIGRATE or GENERATE)
- Entity model extracted/defined with all fields and constraints
- Target format selected and type mappings applied
- Seed data files generated with faker-based realistic values
- Deterministic seeding verified (re-run produces identical output)
- Foreign keys reference valid parent IDs
- Names follow target format conventions
- Sample data includes 5-10 items per entity
Risk Mitigation
| Risk | Detection | Mitigation |
|---|
| Unknown ORM type | Auto-detection fails | Log warning, ask orchestrator for ORM hint |
| Invalid type mapping | Unknown column type | Use string as fallback, log warning |
| FK mismatch | FK references non-existent ID | Generate parents first, validate after |
| No entity list in GENERATE | Empty input | Use starter template (User, Role) |
| Name collision | Duplicate class/table names | Prefix with feature name |
| Circular references | Self-referencing with cycles | Limit depth, validate graph |
Reference Files
| File | Purpose |
|---|
references/orm_patterns.md | ORM auto-detection and schema parsing patterns (Drizzle, Prisma, TypeORM, EF Core, SQLAlchemy, Django) |
references/type_mapping.md | Universal type mapping (ORM-agnostic → C#, TypeScript, Python) + Faker integration |
references/data_generation.md | Realistic sample data patterns and generation rules |
references/relationship_mapping.md | FK handling, generation order, relationship inference |
Version: 3.0.0 Last Updated: 2026-02-07
