Content
78%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.
The content is a lean, actionable recipe with concrete CLI commands, a sensible two-phase workflow, and an approval checkpoint, well-structured for a single-purpose skill. Its main weakness is the absence of error-handling guidance for failed generations.
Suggestions
Add a brief error-recovery step for failed or low-quality generations (e.g., re-run with adjusted prompt or aspect ratio) to strengthen the workflow's feedback loop.
Specify the concrete endpoint path for the curl fallback so the fallback is fully copy-paste ready.
Optionally note how to verify the 3D result looks correct before proceeding to animation.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is efficiently organized with an inputs table, two concise phases, and a compact notes section; the only padding is descriptive prompt text, which is justified since it is the literal generation prompt. | 4 / 5 |
Actionability | Provides concrete executable commands ('muapi image edit' model='nano-banana-2-edit', 'muapi video from-image' model='veo3.1-fast-image-to-video') plus a fallback curl-with-polling pattern, with only minor gaps such as exact endpoint paths for the curl fallback. | 4 / 5 |
Workflow Clarity | Two phases are clearly sequenced with an explicit approval checkpoint ('Present the 3D logo to the user for approval') between them, though it lacks an error-recovery feedback loop for failed API generations. | 4 / 5 |
Progressive Disclosure | A short, single-purpose skill with no external bundle files and no need for references; it is well-organized into clearly labeled sections (Inputs, Steps, Trigger Keywords, Notes), meeting the simple-skill exception for a top score. | 5 / 5 |
Total | 17 / 20 Passed |