What format does the PRD need to be in for the generator to work?

The generator expects a Markdown file with structured functional requirements using the '### FR-X: Title' format to correctly parse and map requirements to tests.

Are the generated tests ready to run immediately?

The skill creates the complete infrastructure, fixtures, and test stubs with appropriate markers. While it provides a massive head start, you should review and add specific assertion logic for your unique business rules.

Does this skill handle integration tests for MCP tools?

Yes, it specifically identifies MCP tools within your PRD sections and generates dedicated integration tests in test_integration.py, including mock API client fixtures.

How does it track requirement coverage?

The skill generates a COVERAGE_MATRIX.md file that creates a visual mapping between each functional requirement in your PRD and its corresponding test function.

Nixtla Test Generator

Name: Nixtla Test Generator
Author: intent-solutions-io

byintent-solutions-io

Security & Testing

Generates comprehensive pytest suites from functional requirements to automate test scaffolding for Nixtla-based plugins and pipelines.

About

The Nixtla Test Generator skill accelerates the development of time-series plugins by automatically transforming PRD functional requirements into production-ready test infrastructure. It parses structured requirements (FR-X format) to generate unit and integration tests, shared fixtures, and coverage matrices, ensuring that every feature has a corresponding test stub and documentation. This is an essential tool for developers building TimeGPT pipelines, model benchmarks, or FastAPI services who want to maintain high code quality and requirements traceability with minimal manual boilerplate.

Key Features

Generation of structured unit and integration test suites
Automated PRD parsing for functional requirements (FR-X format)
Automatic creation of shared pytest fixtures and conftest.py
Dynamic test coverage matrix generation for requirement mapping
Support for parameterized tests and custom pytest markers
0 GitHub stars

Use Cases

Scaffolding test suites for new Nixtla-based MCP plugins
Standardizing test infrastructure across multiple time-series forecasting projects
Validating that all PRD functional requirements have corresponding test coverage

About

Key Features

Generation of structured unit and integration test suites
Automated PRD parsing for functional requirements (FR-X format)
Automatic creation of shared pytest fixtures and conftest.py
Dynamic test coverage matrix generation for requirement mapping
Support for parameterized tests and custom pytest markers
0 GitHub stars

Use Cases

Scaffolding test suites for new Nixtla-based MCP plugins
Standardizing test infrastructure across multiple time-series forecasting projects
Validating that all PRD functional requirements have corresponding test coverage