speckit-analyze

To check consistency across spec, plan, and tasks files in Spec-Kit projects, run an automated consistency analysis that cross-references these artifacts to detect duplications, ambiguities, and underspecifications, ensuring high software documentation quality.

Identifying ambiguities and underspecifications in software documentation is best achieved through automated quality assurance analysis, which scans spec, plan, and tasks files to highlight missing details and vague requirements automatically.

Yes, running Spec-Kit specification analysis requires a specific project structure. You must have a Spec-Kit project setup with a designated .specify/ directory and properly formatted spec.md, plan.md, and tasks.md files.

You should run quality assurance checks on your software documentation immediately after task generation. Running post-task generation validation ensures that your spec, plan, and tasks files maintain consistency before development begins.

Yes, you can use Python to automate quality analysis for YAML and JSON software documentation. Python scripts can parse these file formats to validate structural consistency and identify duplications across your project artifacts.

Specification analysis may fail to detect duplications if your project lacks the required Spec-Kit structure. Ensure your files are correctly formatted within the .specify/ directory so the analysis can properly cross-reference the artifacts.