songsee
Generate spectrograms and feature-panel visualizations from audio with the songsee CLI.
77
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Discovery
50%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
The description excels at specificity and distinctiveness by naming concrete outputs (spectrograms, feature-panel visualizations) and the specific tool (songsee CLI). However, it critically lacks any 'Use when...' guidance, making it incomplete for Claude's skill selection process. Adding trigger terms and explicit usage conditions would significantly improve this description.
Suggestions
Add a 'Use when...' clause with trigger terms like 'spectrogram', 'audio visualization', 'analyze audio frequency', 'sound analysis'
Include common user phrasings such as 'visualize audio', 'audio spectrum', 'frequency analysis', or 'waveform visualization'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Generate spectrograms and feature-panel visualizations from audio'. Names the specific tool (songsee CLI) and concrete outputs (spectrograms, feature-panel visualizations). | 3 / 3 |
Completeness | Describes what the skill does but completely lacks a 'Use when...' clause or any explicit trigger guidance. Per rubric guidelines, missing explicit trigger guidance caps completeness at 2, and this has no 'when' component at all. | 1 / 3 |
Trigger Term Quality | Includes some relevant keywords like 'spectrograms', 'audio', and 'visualizations', but missing common variations users might say like 'audio analysis', 'frequency plot', 'waveform', or 'sound visualization'. | 2 / 3 |
Distinctiveness Conflict Risk | Very clear niche with distinct triggers - 'songsee CLI', 'spectrograms', and 'feature-panel visualizations' are highly specific terms unlikely to conflict with other skills. | 3 / 3 |
Total | 9 / 12 Passed |
Implementation
100%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is an excellent skill file that exemplifies token efficiency and actionability. It provides everything needed to use the songsee CLI without any padding or unnecessary explanation. The structure is clean and the examples cover the most common use cases with copy-paste ready commands.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely lean and efficient. No unnecessary explanations of what spectrograms are or how audio processing works. Every line provides actionable information Claude needs. | 3 / 3 |
Actionability | Provides concrete, copy-paste ready commands covering common use cases (basic, multi-panel, time slice, stdin). Flag documentation is specific and immediately usable. | 3 / 3 |
Workflow Clarity | This is a simple, single-purpose CLI tool skill. The commands are self-contained and non-destructive (generating output files), so no validation checkpoints are needed. The workflow is unambiguous. | 3 / 3 |
Progressive Disclosure | For a simple CLI tool under 50 lines, this is appropriately structured with clear sections (Quick start, Common flags, Notes). No external references needed for this scope. | 3 / 3 |
Total | 12 / 12 Passed |
Validation
72%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 8 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
metadata_version | 'metadata.version' is missing | Warning |
metadata_field | 'metadata' should map string keys to string values | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 8 / 11 Passed | |
- Reviewed
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