songsee
songsee is an Audio, music & podcasts skill for AI agents, published by NousResearch in the hermes-agent repository on GitHub. Skillspace rates songsee C (77/100) and it passed the safety scan; a judge model has also reviewed it.
Audio spectrograms/features (mel, chroma, MFCC) via CLI.
- Grade
- C
- Quality
- 77 / 100
- Safety
- Passed
- GitHub stars
- 244,130
Placed #3 of 6 in the judged category final for Audio, music & podcasts.
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, so go by its current files.
Our review
- Architecture
- 94 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
Judge review
Placed #3 of 6 in the judged category final for Audio, music & podcasts.
- Trigger
72 72 - Instructions
85 85 - Specificity
88 88 - Safety
85 85 - Disclosure
80 80 - Maintenance
70 70
Well-documented spectrogram CLI wrapper with install prerequisites and a definitions table for all nine visualization types, though it's an analysis tool rather than a generation or production skill.
More complete than its sibling variant: adds Go-install prerequisites, a definitions table for all nine visualization types, and concrete downstream-use notes the other version omits.
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- 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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