Generate a FastAPI mock server from API.md and SCHEMA.md documentation.
npx skills add https://github.com/ibalasite/gendoc --skill gendoc-gen-mock
Please help me install this Agent Skill. Skill: gendoc-gen-mock Source: https://github.com/ibalasite/gendoc/tree/main/skills/gendoc-gen-mock Command: npx skills add https://github.com/ibalasite/gendoc --skill gendoc-gen-mock
Automates end-to-end generation of a FastAPI mock server from API documentation (API.md and SCHEMA.md), including mock data, main.py, dependencies, and a usage guide in docs/blueprint/mock.
Run the D18-MOCK workflow to generate a FastAPI mock server from API docs and review the generated docs under docs/blueprint/mock.
High-intent search queries and answers about installing and using this skill.
You can generate a FastAPI mock server from API documentation by running the D18-MOCK workflow, which parses API.md and SCHEMA.md to automatically create a runnable main.py, mock data, dependencies, and a usage guide.
Yes, the generated mock server provides deterministic mock responses and runnable endpoints with health checks, scenario parameters, and delay/error controls, making it fully suitable for frontend testing, demos, and CI integration.
Automating mock data generation works by parsing API.md and SCHEMA.md to extract endpoints, schemas, and resource groups, then producing realistic mock data and empty datasets alongside typed Pydantic models for each resource.
No, you do not need to write Pydantic models manually. The generation process automatically produces a FastAPI main.py with typed Pydantic models, CRUD-style routes, and a reusable data loader based on your API documentation.
The best way to set up a mock server with scenario and delay parameters is to generate a production-grade FastAPI mock server from your API docs, which natively includes health endpoints, error parameters, and structured outputs for testing.
The generation process relies on properly structured API.md and SCHEMA.md files to extract endpoints and schemas; if your API documentation is incomplete or unstructured, the generated mock server and data models may not function correctly.
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