A
licenseB
qualityB
maintenanceProvides video and audio manipulation tools powered by FFmpeg, enabling AI assistants to perform media operations such as cutting, converting, and removing silence.
6
169 npm
2
MIT
mediakit
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TDQS
A3.6/5.0
Scored across 11 tools
Disambiguation5/5
Each tool targets a clearly distinct media operation: probing, converting, concatenating, trimming, cropping, resizing, audio extraction, frame extraction, thumbnails, loudness normalization, and caption burning. Overlaps such as trim vs. extract_frame and thumbnail vs. extract_frame are resolved by their descriptions and output types.
Naming Consistency4/5
Most tools use a consistent snake_case verb_noun or verb pattern: concat, burn_captions, convert, probe, trim, crop, resize, extract_audio, extract_frame. The nouns thumbnail and loudness are minor deviations, though they remain readable and predictable.
Tool Count5/5
Eleven tools is well-scoped for a media processing toolkit, covering common ffmpeg workflows without excessive fragmentation. Each tool has a clear job and none feels redundant.
Completeness4/5
The surface covers most core media lifecycle operations: inspect, convert, trim, concat, crop, resize, extract audio/frames, thumbnail, loudness, and captions. Minor gaps exist, such as replacing or muxing separate audio/video tracks and extracting embedded subtitles, but agents can work around many of these with existing tools.
Maintenance
ActivityMaintained
ResponsivenessNo recent community issues