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Fetch timestamped captions for a YouTube, TikTok, or Instagram URL when the platform provides them. Use segment start_sec/end_sec (or the flat text) to choose a cut range, then call cut_audio with the same URL and those times. When available is false there are no captions — do not invent lyrics or timestamps; tell the user to pick times another way. Optional lang is a BCP-47 code (default en). No job_id is returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesYouTube, TikTok, or Instagram URL to fetch captions for
langNoOptional BCP-47 caption language (default en)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
langYes
textYes
sourceYes
segmentsYes
availableYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so safety is covered. The description adds genuinely new behavior beyond the annotations: caption availability is conditional on the platform, the available=false case must not be hallucinated around, and lang defaults to en. The 'No job_id is returned' note is useful but only marginally so given an output schema exists.

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?

Front-loaded with the core action, then the chaining instruction, then the failure guard, then two small footnotes. No sentence is filler; each adds a distinct operational fact.

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?

Beyond the schema and annotations, the description supplies the workflow handoff to cut_audio and explains how to consume the returned segments, which is exactly what an agent needs for a step in a multi-tool pipeline. An output schema exists, so return-value documentation is correctly not duplicated.

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 coverage is 100%, so both url and lang are already documented at the same level the description restates (BCP-47, default en). The start_sec/end_sec references describe output segments rather than input parameters, so they help context but not parameter semantics. Baseline 3 is correct when the schema carries the parameter burden.

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 and resource (fetch timestamped captions) plus the scope of supported platforms (YouTube, TikTok, Instagram) and the conditional 'when the platform provides them'. It also positions itself in the workflow relative to the only sibling, cut_audio, so an agent can tell the two apart without opening either schema.

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

Usage Guidelines5/5

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

Explicitly routes the agent: use segment start_sec/end_sec to choose a cut range, then call cut_audio with the same URL and those times. It also defines the failure path — when available is false, do not invent lyrics or timestamps and tell the user to pick times another way. This is when-to-use, how-to-chain, and when-not behavior in one place.

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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