Content
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill body is token-efficient and well-structured, but its guidance is procedural rather than executable and its workflows lack validation checkpoints. Providing runnable commands/scripts and an explicit validate-and-verify loop would raise actionability and workflow clarity.
Suggestions
Replace the descriptive numbered mode procedures with executable commands or scripts, or ship the referenced /design-system CLI in scripts/ so the example invocations are real.
Add an explicit validation/verification checkpoint to the generation workflow (e.g., confirm tokens render in the preview, re-run audit to verify scores improved).
Keep the lean, list-driven structure and section organization — it already meets the conciseness and progressive-disclosure anchors.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and list-driven, assuming Claude's competence — it does not explain what design systems, contrast ratios, or AI slop are, so every token largely earns its place. | 3 / 3 |
Actionability | Guidance is concrete and specific (named dimensions, output filenames, example invocations), but the mode procedures are descriptive checklists/pseudocode rather than executable code, and the /design-system CLI is referenced with no bundled implementation. | 2 / 3 |
Workflow Clarity | Multi-step processes are clearly sequenced (numbered 1-6 generation, 1-10 audit dimensions), but there are no validation checkpoints or error-recovery feedback loops, leaving checkpoints missing or implicit. | 2 / 3 |
Progressive Disclosure | A single self-contained file with no external references, organized into clear sections (When to Use, How It Works with three modes, Examples); per the simple-skill carve-out this satisfies the well-organized-sections anchor. | 3 / 3 |
Total | 10 / 12 Passed |