Agent Tools

video_transcribe

Video to transcript: transcribe the speech in a video file at a URL (MP4, MOV, WebM, MKV with an audio track; max 20 MB) with Whisper large v3 turbo. Returns full text, language, duration, timestamped segments and WebVTT captions ready for subtitles. task=translate gives English text. Price $0.03 USDC per call via x402. Example output: {"text":"Hello and welcome to the show.","language":"en","duration_seconds":4.2,"task":"transcribe","format":"mp4","bytes":67000,"word_count":6,"segments":[{"start":0,"end":4.2,"text":"Hello and welcome to the show."}],"model":"whisper-large-v3-turbo"}

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": {
      "url": "<url>"
    },
    "name": "video_transcribe"
  }
}

Input Schema

Name	Required	Description
`url`	Yes	Public URL of the media file itself
`vad`	No	true to apply voice activity filtering
`task`	No
`language`	No	Optional ISO code, e.g. en

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 31, 2026

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 discloses key behavioral traits: price ($0.03 USDC per call via x402), a hard size limit (20 MB), supported formats, output shape with an example, and task=translate semantics. It omits auth/error-handling details but is otherwise transparent.

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?

A dense but front-loaded paragraph: purpose and format details come first, and the example output—though long—earns its place because no output schema exists. No filler sentences.

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?

Given no output schema and no annotations, the description supplies return structure, an example output, cost, and size limits. It leaves vad semantics and x402 workflow details unexplained, but is otherwise complete for calling the tool correctly.

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?

Schema description coverage is 75%, so the baseline is 3. The description adds meaning for task=translate (English output) and URL constraints, but never mentions the vad parameter, so it only partially compensates for the gap.

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?

States a specific verb (transcribe) and resource (speech in a video file at a URL), lists supported formats (MP4, MOV, WebM, MKV with audio), and names the model used. The video-specific scoping implicitly distinguishes it from the audio_transcribe sibling, so an agent can tell what this tool does without opening the schema.

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?

Provides useful context—format constraints, max 20 MB, cost, and task=translate behavior—but never explicitly says when to use this tool versus audio_transcribe or other siblings. Usage is implied rather than routed.

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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