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transcribe_file

Transcribe local audio or video files to text with whisper.cpp, returning the full transcript and optional timestamped segments for further analysis.

Instructions

Transcribe a local audio/video file with whisper.cpp. Returns the transcript text and optional segments.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesLocal path to the audio/video file.
modelNoPath to a .ggml whisper model, or a name hint.
languageNoLanguage code: 'en', 'zh', 'auto' (default: auto).
translateNoTranslate non-English speech into English.
timestampsNoInclude [start --> end] segment boundaries.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It mentions that it uses whisper.cpp and returns transcript text and optional segments, but does not disclose potential side effects (e.g., model downloading), resource usage, or limitations (e.g., file size, format support). It does not describe the structure of the return or whether the operation is read-only or performs writes. This is a minimal disclosure that fails to cover important behavioral aspects.

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?

The description is a single sentence that front-loads the main action and resource. It is concise and avoids verbosity. It mentions the return type in a compact way, though it could be more structured. It earns a high score for efficiency and clarity, but loses a point for not fully leveraging the space to provide more guidance.

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

Completeness2/5

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

For a tool with 5 parameters, no output schema, and no annotations, the description is insufficient. It does not explain how the optional segments relate to the 'timestamps' parameter, does not clarify the behavior of 'translate' or 'language', and does not describe the output format beyond 'transcript text and optional segments'. An agent would need to infer the return structure and the exact effects of parameters, which is risky. The description should provide more operational detail, such as whether the model must be pre-downloaded, the expected input formats, and the exact structure of the return.

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

Parameters3/5

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

The schema description coverage is 100%, meaning all parameters are documented in the schema. The description adds little beyond that: it restates that the file is local, which is already in the schema. It does not clarify the semantics of 'model', 'translate', or 'timestamps' beyond what the schema provides. Since the schema already covers the parameters well, the description's marginal contribution warrants the baseline score of 3.

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

Purpose4/5

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

The description clearly states the verb 'Transcribe' and the resource 'local audio/video file', and mentions the engine (whisper.cpp) and the return of transcript text and optional segments. It is specific but does not explicitly differentiate from the sibling 'transcribe_media', leaving ambiguity about when to use which. Thus it is clear but not fully distinguishing.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus the sibling 'transcribe_media' or 'fetch_media'. The description only states that it works on local files, implying a distinction from remote media, but does not explicitly state when to choose this tool or what the alternatives are. This leaves the agent without clear decision criteria.

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