Content
68%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A solid, mostly actionable skill body backed by a real bundle script, with good progressive disclosure. The main weakness is the Workflow section, which lists abstract steps without validation or feedback loops for a batch generation operation.
Suggestions
Add explicit validation checkpoints to the Workflow (e.g., verify generated features each have testable acceptance criteria, confirm 50-100+ count, and re-decompose if undersized) with a fix-and-retry loop.
Make the Quick Start snippet self-contained by showing how `spec` is obtained or noting the expected input type, so the example is copy-paste ready.
Consider moving the full Feature List Schema into a separate reference file and keeping only a minimal example inline to tighten conciseness.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean body that avoids explaining concepts Claude already knows, though the inline Feature List Schema JSON and the Categories/Priority lists could be slightly trimmed to earn the top anchor. | 4 / 5 |
Actionability | Provides an executable Quick Start snippet importing the real SpecGenerator class and delegates the bulk to scripts/spec_generator.py, leaving only minor gaps versus fully copy-paste-ready coverage. | 4 / 5 |
Workflow Clarity | The six-step Workflow (Parse, Analyze, Decompose, Prioritize, Enrich, Export) is sequenced but described abstractly with no validation/verification checkpoints for a batch generation of 50-100+ features, capping it at 3. | 3 / 5 |
Progressive Disclosure | Well-organized sections with a clearly signaled one-level reference to the real bundle file scripts/spec_generator.py for full implementation; the inline schema is acceptable as core content, leaving only minor organization gaps. | 4 / 5 |
Total | 15 / 20 Passed |