AC phy-test-data-factory
Schema-driven test data factory generator. Reads your database schema or model definitions — Prisma schema, SQLAlchemy models, Django models, TypeORM entities, Zod schemas, Pydantic models, or raw SQL DDL — and generates ready-to-use factory functions with realistic fake data. Outputs TypeScript factory files using Faker.js, Python conftest.py using factory_boy + Faker, or raw SQL INSERT seed scripts. Respects foreign key relationships (seeds parents before children), handles enums, nullable fields, unique constraints, and generates edge-case variants (empty strings, max-length values, boundary dates). Zero external API — pure local file analysis + code generation. Triggers on "generate test data", "seed database", "test fixtures", "factory functions", "fake data from schema", "/test-data-factory".
Schema-driven test data factory generator.
As a process C 53/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 5266 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 53/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 12 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 70Execution cost. Instruction body is 5266 tokens
- 100Steps. 6 steps
- 100Consistency. Name and required fields are in place
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 809: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +5Description quotes 6 example trigger phrases
- +4Structure: 15 headings
- +3Step-by-step instructions: 6 items
- +4Has examples (12 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.