Content
87%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-structured, concise, actionable skill body with strong progressive disclosure and a clear default workflow. The main gap is missing explicit validation checkpoints for batch and destructive operations.
Suggestions
Add an explicit validation checkpoint to the workflow before generation (e.g., verify avatar_id and voice_id exist via GET /v2/avatars and /v2/voices before POST /v2/video/generate) rather than only mentioning it as a best practice.
For batch generation, include a confirmation/quota-check step (e.g., check credits via references/quota.md) before issuing multiple POST /v2/video/generate calls.
For the delete_video operation, add an explicit confirm-before-delete checkpoint to satisfy the destructive-operation feedback-loop requirement.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean and efficient: each section earns its place with no padding explaining what avatars/voices/MCP are, and detailed material is offloaded to reference files rather than inlined. | 3 / 3 |
Actionability | Provides an executable curl example with the real X-Api-Key header and endpoint, exact HTTP methods/paths in the workflow, and concrete tool names in the selection table; best practices cite specific fields like test: true and preview_image_url. | 3 / 3 |
Workflow Clarity | The Default Workflow is a clear numbered 5-step sequence with endpoints and a polling termination condition, but destructive (delete_video) and batch operations named by the description lack explicit validation checkpoints, which caps this dimension at 2 per the rubric. | 2 / 3 |
Progressive Disclosure | Overview body points to one-level-deep references; both 'Quick Reference' and 'Reference Files' tables map tasks to markdown links, and all 15 referenced files verified to exist with clear organization by category. | 3 / 3 |
Total | 11 / 12 Passed |