create-testcase

To generate a QC test skeleton, the skill reads docs like user_stories.md and conceptual_model.md to assemble a JSON linking all user stories and acceptance criteria with empty test case arrays. This deterministic output provides a ready-to-edit baseline for downstream test case writing.

Ensuring test coverage during QC planning requires a structured skeleton with coverage indices for domain rules, change items, and routes. The generated JSON captures these indices to support gap analysis and traceability, preventing missed acceptance criteria.

Creating a traceability matrix in JSON involves mapping user stories to acceptance criteria with empty test case arrays. The skill outputs this structure at tasks/qc/testcases-skeleton.json, including metadata about source IDs and status for manual or automated test expansion.

Yes, you can build empty test case arrays from markdown documentation. The skill reads markdown files like user_stories.md and changes documentation to generate a deterministic JSON skeleton, serving as a ready-to-edit baseline for manual test case expansion.

Automated test skeleton generation requires reading docs/user_stories.md, docs/conceptual_model.md, docs/ia_structure.md, and docs/changes/<id>.md. These source files provide the user stories, acceptance criteria, and domain rules needed to assemble the test structure.

Generating a test case skeleton explicitly supports gap analysis for change items by including dedicated coverage indices. The output JSON captures all relevant change items alongside domain rules and routes to ensure comprehensive QC coverage planning.