Content
82%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 highly actionable with executable commands, templates, and tables, and the workflow is clearly sequenced with a quality checklist, but it keeps everything inline rather than offloading reference material to separate files and lacks explicit output-validation checkpoints.
Suggestions
Add an explicit validation/feedback step before video generation, e.g. verify the reference image file exists and rendered before passing it via --file.
Move the Camera Language Reference and Platform Specs tables into reference files (e.g. references/camera-language.md, references/platform-specs.md) and link to them from the body to improve progressive disclosure.
Trim the worked example and the playful/premium tone illustration to tighten token efficiency.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and mostly tabular (platform specs, camera intents, model tables, templates) and assumes Claude's competence without explaining concepts, but has minor trimmable padding such as the playful/premium tone example and the long worked example. | 4 / 5 |
Actionability | Provides fully executable, copy-paste-ready commands (generate-image.sh and run-social-video.sh, the latter verified present in scripts/), a Director Brief template, mode/model selection tables, and a complete worked example covering the common cases. | 5 / 5 |
Workflow Clarity | A clear 5-step Agent Execution Protocol is sequenced with a Prompt Quality Checklist as a checkpoint, but there is no explicit validate-output or feedback loop (e.g., confirming the reference image rendered before invoking video generation). | 4 / 5 |
Progressive Disclosure | Well-organized with clear section headers and a single clearly-referenced bundle script (scripts/run-social-video.sh); however all ~278 lines are inline with no references/ or assets/ files, and the camera-language/platform tables could be split out for a skill of this size. | 4 / 5 |
Total | 17 / 20 Passed |