Content
70%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The content is a well-sequenced, self-contained interview-to-PRD workflow with strong workflow clarity and organization. Its weaknesses are minor unnecessary explanation of a known concept and missing concrete mechanics for file creation and issue submission.
Suggestions
Remove or shorten the 'deep module' definition — Claude already knows the deep-vs-shallow module distinction, so a one-word cue suffices.
Add a concrete step for producing the artifact, e.g. write the PRD to `./ai-context/prds/<name>.md` and submit with `gh issue create --title ... --body-file ...`.
Make the completion gate before writing the PRD crisper than 'Once you have a complete understanding' — e.g. an explicit checklist the user must confirm.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly lean, but the parenthetical 'A deep module (as opposed to a shallow module) is one which encapsulates a lot of functionality...' explains a software-design concept Claude already knows, so it could be tightened. | 2 / 3 |
Actionability | The PRD template and step sequence are concrete, but the mechanics are incomplete — there is no command or method for creating the markdown file or submitting the GitHub issue (e.g., a `gh issue create` invocation). | 2 / 3 |
Workflow Clarity | A clearly numbered 1–5 sequence with explicit user-confirmation gates ('Check with the user that these modules match their expectations' and 'Once you have a complete understanding...') serving as the feedback loops appropriate for an interview/planning skill. | 3 / 3 |
Progressive Disclosure | No bundle files exist and none are needed; the skill is self-contained and organized into numbered steps plus a clearly delimited template block, which is appropriate for a reference-free skill. | 3 / 3 |
Total | 10 / 12 Passed |