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mcp-tools-for-agents

mcp-tools-for-agents

by theGuil
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Rust
Local

transcribe_audio

Transcribe speech from audio or video files with per-segment timestamps. Use transcripts to locate and cut video by spoken content.

Instructions

Transcreve a fala de um áudio ou vídeo, com tempos de cada trecho.

Combine com cut_video para cortar por conteúdo falado. É lento, por isso roda em background por padrão.

Args: path: Áudio ou vídeo, relativo ao workspace. model_size: Modelo whisper: tiny, base, small, medium ou large-v3. language: Código do idioma (pt, en). Detecta automaticamente se omitido. background: Executa como job e devolve job_id.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "path": "<path>"
    },
    "name": "transcribe_audio"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYes
languageNo
backgroundNo
model_sizeNobase

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden and does well: it discloses that the operation is slow, runs as a background job by default, returns timestamps, and can auto-detect language. It could add more detail about job lifecycle or blocking behavior when background=false, but the key traits an agent needs are present.

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 compact and front-loaded: purpose first, then collaboration guidance, then the important performance/background note, then concise parameter definitions. Every sentence adds value and nothing is redundant with the schema.

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 4-parameter transcription tool with an output schema present, the description covers the required input semantics, the behavioral caveats, and the relevant sibling collaboration. An agent has enough information to call the tool correctly and interpret the background-job behavior.

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?

Schema description coverage is 0%, so the description must compensate, and it does thoroughly: path is specified as relative to workspace, model_size enumerates the available Whisper options, language gives example codes and clarifies auto-detection, and background is explained as running as a job and returning job_id. Every parameter gains meaning beyond the raw schema.

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 opens with a specific verb and resource: 'Transcreve a fala de um áudio ou vídeo, com tempos de cada trecho,' making it clear this tool produces a timestamped transcript. It also distinguishes itself from sibling tools by positioning it as the companion to cut_video for content-based cutting, so an agent can tell it apart from tools like probe_video or extract_audio.

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 gives clear usage context: use it to transcribe speech and combine it with cut_video when cutting by spoken content. It also warns that the tool is slow and therefore runs in background by default, helping an agent set expectations. It does not explicitly name when-not-to-use alternatives, but no direct alternative transcription tool exists among the siblings.

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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