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transcribe_to_file

Transcribe audio recordings and export the text to a subtitle or text file. Specify the output path and format (SRT, VTT, or TXT) to generate a readable transcript.

Instructions

[EXPERIMENTAL] Transcribe audio and export to a subtitle or text file. Requires separate setup — see installation guide.

ALWAYS tell the user where the file will be saved BEFORE starting. If user doesn't specify a path, call get_default_export_folder to get a real path. NEVER guess paths like /home/user/... — always use absolute Windows paths like C:\Users\Name\Documents\transcript.srt

Runs in BACKGROUND — returns a job_id immediately. Use check_transcription_status to monitor progress.

Language auto-detection can occasionally misidentify the language (background music, noise, a short/ambiguous clip) and transcribe genuinely-English audio in the wrong script entirely. If you already know the audio's language from context, pass language explicitly (e.g. "en"), or set task="translate" to force English output regardless of the spoken language. Retry with THIS SAME tool and the corrected language/task — use a new path since an existing file at the same path is rejected below.

Args: path: Absolute path for the output file (e.g. "C:/Users/You/Documents/transcript.srt") format: Output format - "srt", "vtt", or "txt" model_size: Whisper model - "tiny", "base", "small", "medium", "large-v3" language: ISO language code (e.g. "en") or None for auto-detect task: "transcribe" (spoken language) or "translate" (always English)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
taskNotranscribe
formatNosrt
languageNo
model_sizeNosmall
Behavior5/5

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

With no annotations, the description carries the full burden and does exceptionally well. It discloses the experimental status, separate setup requirement, background execution returning a job_id, rejection of existing files, and the language auto-detection pitfall. It also instructs on absolute Windows paths, which is critical for correct usage.

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

Conciseness5/5

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

The description is well-structured and front-loaded. It opens with the purpose, followed by critical usage warnings, then a detailed but relevant parameter breakdown. Every sentence adds value—path safety, background behavior, and language pitfalls are all crucial for an experimental tool. No filler.

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

Completeness5/5

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

For a complex background transcription tool with no output schema or annotations, the description covers all necessary context: setup, file path handling, monitoring via sibling tool, error on existing file, and language misidentification. It even explains retry strategy with corrective parameters. The absence of output schema is mitigated by mentioning the job_id and pointing to check_transcription_status.

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

Parameters5/5

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

The input schema has 0% coverage (no property descriptions), but the description's 'Args' section provides detailed semantics for every parameter: absolute path format, format options, model_size options, language code meaning, and task options. This fully compensates for the schema's lack of descriptions.

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's function: 'Transcribe audio and export to a subtitle or text file.' It uses a specific verb ('transcribe') and resource ('audio' to 'file'), and immediately distinguishes itself from siblings by noting it runs in the background and writes to a file, unlike transcribe_audio or transcribe_to_labels.

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?

Provides explicit workflow guidance: ALWAYS tell the user where the file will be saved, call get_default_export_folder when no path is given, and use check_transcription_status to monitor progress. However, it does not explicitly contrast with alternative transcription tools like transcribe_audio or transcribe_selection, so it lacks explicit when-not-to-use guidance.

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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