songsee
songsee is an Audio, music & podcasts skill for AI agents, published by HKU-MMLab in the UniClawBench repository on GitHub. Skillspace rates songsee D (65/100) and it was flagged as an attack benchmark; the rating is based on static analysis only.
Flagged as an attack benchmark: test cases written to attack AI agents. Do not install or run it.
Generate spectrograms and feature-panel visualizations from audio with the songsee CLI, and pull out music-information-retrieval features such as tempo, key, beat grid, and section boundaries.
- Grade
- D
- Quality
- 65 / 100
- Safety
- Flagged as an attack benchmark
- GitHub stars
- 34
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since.
Our review
- Architecture
- 94 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- The static scan found no issues, but it was flagged as an attack benchmark.
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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