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Finekot API

speech_to_text

Transcription with timestamps and language detection, 99 languages. Input: url or file (mp3, m4a, wav, ogg, webm, mp4) up to 25 MB / 30 min. Output: text, segments, optional SRT/VTT. Billed per started minute. Cost €0.004 per minute, charged to the API key in Authorization: Bearer. Parameters — url: string (audio/video url); language: ISO code, e.g. en, ru, uk (default: auto); translate: bool — translate to English; format: json | srt | vtt (default json, adds subtitles field).

Input Schema

NameRequiredDescriptionDefault
urlNo
formatNo
languageNo
translateNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses billing per started minute, the exact price, that charges go to the API key in the Authorization: Bearer header, and hard input limits. It stops short of latency/sync-vs-async behavior and error modes, which would be needed for a 5.

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?

One dense but well-ordered passage with explicit Input/Output/Parameters sections and no filler; the most decision-relevant facts (what it does, limits, cost) are front-loaded.

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

Completeness4/5

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

An output schema exists, yet the description still usefully names the returned fields (text, segments, subtitles), and adds cost, auth and format constraints. The only completeness flaw is the dangling 'file' input reference that has no corresponding schema parameter, which could mislead an agent.

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 coverage is 0%, so the description compensates by documenting every parameter with type, format and default (url, language ISO codes with 'auto' default, translate, format json|srt|vtt). It even supplies the enum values the schema lacks, though it types translate as bool while the schema declares a string, and it mentions a 'file' input for which no parameter exists.

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?

States a specific operation (transcription with timestamps and language detection) over a specific resource (audio/video up to 25 MB / 30 min), with scope of 99 languages. It does not explicitly differentiate itself from near-neighbors in the sibling list such as subtitles, ocr or translate, so it falls short of a 5.

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

Usage Guidelines3/5

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

Usage is only implied through input constraints (supported formats, size/time caps) and the translate flag; there is no explicit 'use this when' or 'use X instead' routing against siblings like subtitles or translate. An agent can infer the context but must reason about alternatives itself.

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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