speckit-specify

Feature specification generation works by translating your natural language feature narrative into a SPEC.md file, filling mandatory sections like objectives, success criteria, and acceptance tests while enforcing standardized template fields.

You create feature specs that follow a standardized template and quality checklist by loading project templates, filling mandatory sections, enforcing frontmatter-driven fields, and validating the resulting spec with a built-in quality checklist.

The best way to reduce ambiguity when creating feature specifications is to translate plain natural language descriptions into precise specs and proactively surface gaps for clarifications during the spec creation process.

Yes, you can customize the spec workflow by loading project templates and applying optional extension hooks to tailor the feature specification generation and validation process to your team's specific requirements.

Validation works by applying a built-in quality checklist to the generated feature specification, surfacing any gaps or missing information, and handling clarifications during spec creation to ensure precision and reduce ambiguity.