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generate_subtitles

Generate subtitle files for audio or video files using local speech recognition. Supports automatic language detection and English translation.

Instructions

Generate subtitle files for an audio or video file using whisper.cpp. Set language='auto' to detect the spoken language automatically. Set translate_to_english=true to also generate an English translation subtitle file. When both are requested, two .srt files are saved: one in the original language (e.g. film.ja.srt) and one English translation (film.en.srt). Load in VLC via Subtitle → Add Subtitle File. Supports all standard formats plus .3gp and .ts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYesAbsolute Windows path to the file.
languageNoLanguage code (e.g. ja, es, fr, de) or 'auto' to detect automatically. Defaults to en.en
translate_to_englishNoAlso generate an English translation .srt alongside the native language .srt. Only applies when language is not 'en'. Not available in background mode.
backgroundNoRun as a detached background job — recommended for files over 10 minutes. Returns a job ID to use with check_progress. translate_to_english is not available in background mode.
threadsNoCPU threads. Defaults to 2 of 2.
temperatureNoSampling temperature 0.0–1.0. Default 0.0.
promptNoPrior context string for domain-specific vocabulary or speaker names.
beam_sizeNoBeam search width. Higher = more accurate, slower. Default 5.
best_ofNoCandidate sequences evaluated. Default 5.
diarizeNoStereo speaker diarization. Requires stereo audio with speakers on separate channels.
vad_modelNoPath to Silero VAD model .bin. Strips silence before transcription. Download via download_model.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations burden the description to disclose behavior. It covers output format (.srt files), background mode, and file format support. Lacks detail on return values for synchronous calls and error handling, but overall informative.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is well-structured with a clear first sentence, then explanation of key options. It is reasonably concise but covers necessary details without being overly verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 11 parameters and no output schema, the description covers main outputs and background return. However, it lacks explicit details on synchronous return values and error cases, leaving some completeness gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers all 11 parameters with descriptions. The description adds value by explaining language='auto', translation behavior, and background mode job ID. Some advanced parameters like temperature and beam_size are only in schema, which is acceptable.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates subtitle files for audio/video using whisper.cpp. It distinguishes from sibling tools like transcribe_audio by focusing on subtitle generation and mentions practical usage like loading in VLC.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use auto language detection and translation, and restricts translate_to_english in background mode. However, it does not explicitly compare with siblings or state when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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