audio-metrics
audio-metrics is an Audio, music & podcasts skill for AI agents, published by wimpysworld in the nix-config repository on GitHub. Skillspace rates audio-metrics D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Load for objective audio analysis from ffmpeg metrics - spectral statistics, spectrograms, loudness, EBU R128, LUFS, LU, RMS, dBFS, dBTP, true peak, crest factor, dynamic range, and noise floor. Covers the aspectralstats, astats, ebur128, and loudnorm filters: what each metric measures, how ffmpeg computes it, its units and range, and the external loudness standards and platform targets. Use when reading or producing ffmpeg audio measurements, even when the user names only a metric, filter, or standard.
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 697
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- BlueOak-1.0.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked 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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