Content
61%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 provides concrete, executable guidance and a clear phased workflow with input validation, but the verbose inlined prompt and missing externalization of the large prompt block limit conciseness and progressive disclosure.
Suggestions
Move the lengthy cinematic prompt block into a references/ file (e.g. PROMPT.md) and reference it from the body to improve progressive disclosure and reduce token weight.
Tighten the scene-timeline prose by removing repeated stylistic qualifiers (e.g. 'cinematic', 'broadcast quality') that restate the Style/Lighting sections.
Add an explicit post-generation validation step (e.g. confirm the predict returned a video URL) before presenting the result to the user.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly efficient but the ~30-line cinematic prompt is heavily padded with descriptive prose that restates the same scene, and the description is duplicated verbatim as a subtitle, which inflates tokens. | 3 / 5 |
Actionability | Concrete CLI command with model id, fallback raw endpoint, exact image ordering, and full parameter set (aspect ratio, duration, resolution, generate_audio) give mostly executable guidance with only minor gaps around curl body construction. | 4 / 5 |
Workflow Clarity | Phases A and B are clearly sequenced with explicit input validation in Phase A, and the 0-15s timeline is broken into labeled segments; minor gap is no explicit validation that generation succeeded before presenting. | 4 / 5 |
Progressive Disclosure | No bundle files exist; the entire large cinematic prompt is inlined in the body rather than split into a separate reference, which is content that clearly belongs in its own file, so structure could be better organized. | 3 / 5 |
Total | 14 / 20 Passed |