create-specification

To generate AI-ready specifications, you need structured Markdown files that define requirements, constraints, and interfaces in clear, machine-readable language. This ensures generative AI models can accurately understand and implement the specified tasks.

Documenting API requirements for AI implementation requires creating comprehensive specification documents that clearly define endpoints, request and response schemas, and error handling. Structured formatting ensures the AI can easily parse the API details.

Creating structured specification files in Markdown format involves defining requirements, constraints, and interfaces within a self-contained document. Using a standardized template ensures consistency and clarity for machine-readable documentation.

No dependencies are required to automate specification generation. The process relies on internal scripts to generate new specification files, saving them directly to a designated directory using a standardized naming convention.

Machine-readable specification files for generative AI should be saved in a dedicated /spec/ directory. The files must follow a naming convention like spec-[a-z0-9-]+.md to maintain organizational structure and accessibility.

You need structured specifications for generative AI projects when defining new APIs or data pipelines. Clear, self-contained documentation with defined constraints and interfaces ensures the AI accurately understands and executes the implementation requirements.