Content
92%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.
Excellent operational content: an executable drop-in workflow, explicit validation and error handling, and well-organized progressive disclosure into real reference files. The only deduction is minor non-operational padding (attribution and date-stamped model recommendations) that slightly dents token efficiency.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and operational with no explanations of concepts Claude already knows, but minor content could be trimmed: the provenance/attribution paragraph about the OpenRouter adaptation, and the date-stamped model recommendations ('Recommendation as of 2026-10-29') — time-sensitive information not placed in an old-patterns/deprecated section. This lands on anchor 4 rather than the every-token-earns-its-place anchor 5. | 4 / 5 |
Actionability | Fully executable throughout: a copy-paste-ready bash workflow with curl + jq, concrete model IDs, parameter-level detail (frame_images shapes, data-URL construction, passthrough JSON examples), and specific error codes (402/400/404/500) with handling guidance. | 5 / 5 |
Workflow Clarity | The async submit → poll → download sequence is explicit with terminal failure states ('failed, cancelled, expired — surface the error field verbatim'), the script validates the submit response and exits with the error on failure, parameters are validated client-side against the models endpoint, and recovery guidance exists (try another model on prompt-filter rejection). | 5 / 5 |
Progressive Disclosure | SKILL.md stays an overview with prompt-crafting detail correctly split into three one-level-deep references (cinematography.md, storytelling.md, example-prompts.md), each clearly signaled with its use case, and all three files exist in the bundle. | 5 / 5 |
Total | 19 / 20 Passed |