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 concise, highly actionable, and well-organized as a single-file skill, but batch image generation lacks validation/error-recovery checkpoints, capping workflow clarity.
Suggestions
Add a verification step after generation (e.g. check each request succeeded and retry failed angles before presenting the grid).
Remove the redundant bold restatement of the description at the top of the body to save tokens.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and assumes Claude's competence: it skips explaining what product photography is and jumps to concrete prompts, model IDs, and CLI calls, with every section earning its place. | 3 / 3 |
Actionability | Provides copy-paste-ready prompts with exact model IDs, aspect ratios, conditional model selection, and a concrete curl fallback plus polling command — fully executable guidance. | 3 / 3 |
Workflow Clarity | The five angles are clearly sequenced for parallel generation, but there is no validation or verification checkpoint (e.g. confirming an image returned or retrying a failed angle), which the rubric requires to score 3 for batch generation. | 2 / 3 |
Progressive Disclosure | A compact single-file skill with no bundle references; sections (Inputs, Steps, Notes, Triggers, Notes for the Executing Agent) are well-organized and easy to navigate, which is appropriate for a sub-50-line single-purpose skill. | 3 / 3 |
Total | 11 / 12 Passed |