Content
87%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The content is highly actionable and concise with strong organization, but the multi-image batch workflow lacks an explicit validation checkpoint for generated output quality.
Suggestions
Promote the brand-name spelling check from Notes into an explicit workflow checkpoint after generation (e.g. 'Review each concept: verify the brand name is spelled correctly before presenting to the user; regenerate if misspelled').
Add an explicit verification step between generation and presentation so the batch operation has a clear validate-then-proceed feedback loop.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and assumes Claude's competence — an inputs table, concrete generation prompts, and terse model-selection notes with no padding or explanation of concepts Claude already knows. | 3 / 3 |
Actionability | Each step gives an executable `muapi image generate` command with a specific model, full prompt text, and aspect ratio, plus a curl fallback — copy-paste ready guidance. | 3 / 3 |
Workflow Clarity | Phases A and B are clearly sequenced with a user-selection checkpoint, but output validation (the 'check brand name spelling' note) is implicit in Notes rather than an explicit checkpoint in the batch-generation workflow, capping this at 2. | 2 / 3 |
Progressive Disclosure | A self-contained, well-organized single file with no bundle files and no need for external references, so the well-structured sections (Inputs, Steps, Notes) earn the top score per the simple-skill guidance. | 3 / 3 |
Total | 11 / 12 Passed |