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Samplecut

by app.samplecut.api
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Fetch timestamped captions for a YouTube, TikTok, Instagram, SoundCloud, or X 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

NameRequiredDescriptionDefault
urlYesYouTube, TikTok, Instagram, SoundCloud, or X URL to fetch captions for
langNoOptional BCP-47 caption language (default en)
contextYesOne short sentence on what the user is trying to do with this audio (for example 'ringtone from the chorus'). No links, names or personal details.
llm_modelYesThe exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
conversation_idNoPass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.

Output Schema

NameRequiredDescriptionDefault
langYes
textYes
sourceYes
segmentsYes
availableYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / url / description
      Previous value: -"YouTube, TikTok, Instagram, or SoundCloud URL to fetch captions for"New value: +"YouTube, TikTok, Instagram, SoundCloud, or X URL to fetch captions for"
  2. Changed1 schema field changed
    • changedInput schema / properties / url / description
      Previous value: -"YouTube, TikTok, or Instagram URL to fetch captions for"New value: +"YouTube, TikTok, Instagram, or SoundCloud URL to fetch captions for"
  3. Changed4 schema fields changed
    • addedInput schema / properties / context
      Added value: +{
+  "description": "One short sentence on what the user is trying to do with this audio (for example 'ringtone from the chorus'). No links, names or personal details.",
+  "type": "string"
+}
    • addedInput schema / properties / conversation_id
      Added value: +{
+  "description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.",
+  "type": "string"
+}
    • addedInput schema / properties / llm_model
      Added value: +{
+  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+  "type": "string"
+}
    • changedInput schema / required
      Previous value: -[
-  "url"
-]New value: +[
+  "url",
+  "context",
+  "llm_model"
+]
  4. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly/openWorld/non-destructive, so safety is covered. The description adds genuinely useful behavior beyond that: captions only exist 'when the platform provides them', the available=false fallback, and the notable fact that no job_id is returned (unlike async job tools). It does not discuss rate limits or per-platform quirks, so not 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four tight sentences, front-loaded with purpose then workflow then failure mode. The only redundancy is repeating lang's BCP-47 default from the schema; otherwise every sentence earns its place.

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?

With an output schema present, return values need not be described, yet the description still explains the available flag and the segment timing fields that drive the next call. Combined with the stated no-job_id fact and the follow-up tool, an agent has everything needed to call it 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 coverage is 100%, so all five parameters are already documented, including lang's BCP-47 default and the context/llm_model/conversation_id instructions. The description mostly restates the lang default and otherwise adds no parameter-level meaning, which is the expected baseline when the schema does the work.

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') and enumerates the exact supported platforms. The tool is clearly a caption-retrieval step that precedes cut_audio, so an agent can distinguish it from siblings 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 Guidelines5/5

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

Explicitly prescribes the workflow: use segment start_sec/end_sec to pick a range, then call cut_audio with the same URL and those times. It also covers the negative case (available=false: tell the user to pick times another way, don't invent lyrics or timestamps), leaving little to inference.

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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