Content
87%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-crafted skill that efficiently teaches music generation with ElevenLabs. It excels at conciseness and actionability with executable examples across three languages, and uses progressive disclosure effectively. The main weakness is the workflow section could benefit from explicit validation steps for verifying generated audio quality or handling streaming errors.
Suggestions
Add a validation step after audio generation (e.g., check file size > 0, verify audio duration matches requested length)
Include error recovery guidance for streaming failures (e.g., what to do if the stream is interrupted mid-generation)
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Content is lean and efficient with no unnecessary explanations. Assumes Claude knows what lo-fi hip hop is, how APIs work, and basic programming concepts. Every section earns its place. | 3 / 3 |
Actionability | Provides fully executable, copy-paste ready code examples in Python, JavaScript, and cURL. Concrete examples with specific parameters (music_length_ms=30000) and real output handling. | 3 / 3 |
Workflow Clarity | The composition plan workflow shows a clear sequence (create plan → inspect/modify → compose), but lacks explicit validation checkpoints. No guidance on verifying the generated audio or handling partial failures in the streaming response. | 2 / 3 |
Progressive Disclosure | Excellent structure with quick start upfront, methods table for overview, and clear one-level-deep references to installation guide and API reference. Content appropriately split between main skill and reference files. | 3 / 3 |
Total | 11 / 12 Passed |