Content
87%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is concise, highly actionable, and well-structured with concrete commands and prompts across three clear phases. Its main gap is the absence of verification checkpoints after the batch image generation, which leaves workflow_clarity capped at 2.
Suggestions
Add an explicit verification step after generation, e.g. confirm each 'muapi predict wait <request_id>' succeeded and retry any failed asset before presenting the guide.
Include a brief error-recovery note for common generation failures (rate limits, rejected prompts) to complete the validate->fix->retry loop.
Optionally note how the four assets should be ordered or titled when presented as a cohesive guide.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and assumes competence — each phase gives a command, model ID, prompt, and aspect ratio with no concept explanation or padding, matching the score-3 'every token earns its place' anchor. | 3 / 3 |
Actionability | Guidance is fully executable: concrete 'muapi image generate' commands with exact prompts, model IDs, aspect ratios, and a curl fallback with polling, making it copy-paste ready. | 3 / 3 |
Workflow Clarity | The three parallel phases are clearly sequenced, but for a batch generation workflow there are no explicit validation/verification checkpoints confirming assets succeeded before presenting them, which per the rubric caps workflow clarity at 2. | 2 / 3 |
Progressive Disclosure | Content is organized into clearly labeled sections (Inputs, Steps, Notes, Trigger Keywords) in a single concise file with no nested references; per the simple-skills scoring note this earns a 3 for well-organized short content. | 3 / 3 |
Total | 11 / 12 Passed |