Universal seed data generator: MIGRATE from ORM schemas or GENERATE from entity definitions to any target format
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Type: L3 Worker Category: 7XX Project Bootstrap Parent: ln-720-structure-migrator
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).
| 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:
| 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).
| 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 |
| 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 |
| 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 |
| 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.
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 |
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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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
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Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA standards. Use this skill to generate semantic ARIA for Web and accessibility traits for Web and Native platforms (iOS/Android).
中文简介正在准备中。当前显示原文说明。
Whole site or product — a full web accessibility (a11y) audit against WCAG 2.2, following the WCAG-EM methodology. Defines scope, samples representative pages and flows, runs the automated tier (`accessibility-scan`) and the hands-on manual tier (`accessibility-inspect`), and produces one conformance report. Grades each finding by severity and evidence basis, and states per-criterion conformance as pass, fail, or undetermined (needs a human). Use it for 'audit my site for accessibility', 'is this product accessible', 'a11y audit', 'WCAG or Section 508 conformance report', or any multi-page assessment. Assesses; does not fix (use `accessibility-fix`) or diff (use `accessibility-diff`). For a single page use `accessibility-scan`; for hands-on keyboard and screen-reader checks use `accessibility-inspect`.
中文简介正在准备中。当前显示原文说明。
Regression check — diff a live page's web accessibility (a11y) violations against a baseline. By default it compares your uncommitted changes (stash-based); pass `--branch [<name>]` to compare against a branch. Reports the new WCAG violations introduced, the ones fixed, and the count of pre-existing ones. Use it for 'did my change break accessibility', 'what a11y issues did this PR add', or as a CI gate. For a full scan of one page use `accessibility-scan`; for a whole site use `accessibility-audit`.
中文简介正在准备中。当前显示原文说明。
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中文简介正在准备中。当前显示原文说明。
One page, hands-on manual tier — drive a live page through the web accessibility (a11y) checks a rule engine can't decide: keyboard operation and focus order, screen-reader names, roles and states from the accessibility tree, reflow and zoom, reduced motion, form errors, and target size. Grades each finding by evidence basis (verified / confirm-with-a-human / human-required) and severity, and closes every criterion in a ledger: verified, flagged, not exercised, or N/A. Locates and assesses; does not fix (use `accessibility-fix`). Use it for keyboard testing, focus-order checks, screen-reader or a11y-tree review, reflow and zoom at 200%, or 'is this operable, not just lint-clean'. The automated tier is `accessibility-scan`; `accessibility-audit` runs both across a sampled site.
中文简介正在准备中。当前显示原文说明。
One page, automated tier — run the web accessibility (a11y) rule engine against a live page and locate every violation it can detect mechanically. Pass a URL, a config target name (e.g. `accesslint:accessibility-scan dev`), or nothing to use the default target from `accesslint.config.json`. Ensures a debuggable Chrome, runs the @accesslint/core engine over CDP, and returns a worklist of live-DOM WCAG 2.2 violations, each grounded to its DOM selector and source `file:line`. Locates; doesn't edit. Use it for 'is this page accessible', 'check a11y on this URL', 'find contrast and alt-text issues', or to verify a UI change. For hands-on keyboard and screen-reader checks use `accessibility-inspect`; for a whole site or product use `accessibility-audit`; to diff against uncommitted changes or a branch use `accessibility-diff`.
中文简介正在准备中。当前显示原文说明。