babelscribe
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TDQS
Scored across 4 tools
Each tool targets a clearly distinct action: list_devices (GPU discovery), list_languages_and_models (model/language info), transcribe (the core operation), and find_media (file discovery). No two tools overlap in purpose, so an agent can select unambiguously.
Consistently snake_case with verb-led names (list_devices, list_languages_and_models, find_media), which is predictable. The lone deviation is 'transcribe', which is verb-only with no noun object, though its meaning is still clear.
Four tools is well-scoped for a transcription server: two read-only discovery helpers, one file-locator helper, and one core action. Nothing feels redundant or missing from the count itself.
The surface covers the full workflow: locate media, inspect devices/models, and transcribe into multiple formats. Minor gaps exist (no batch processing, cancellation, or explicit model-download tool), but agents can work around these.