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FastScribe

Transcribe a public video link

transcribe_url

Transcribes a public YouTube, TikTok, Instagram, X/Twitter, Facebook video from its URL and returns the transcript. Spends credits from the user's FastScribe balance (see get_pricing_and_limits). Private or restricted videos fail and are not charged.

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": "transcribe_url"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYesPublic video URL
formatNotext: plain transcript. timestamped: one line per sentence with [m:ss]. srt: subtitle file.text
languageNoSpoken language code such as "en" or "es". Omit to auto-detect.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare openWorldHint=true, idempotentHint=false, and destructiveHint=false. The description adds genuinely useful context beyond them: each call spends credits (consistent with non-idempotent) and failed private/restricted fetches are not charged. It stops short of describing latency, async behavior, or per-video length limits.

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?

Three tight sentences: capability and platform scope first, then cost disclosure, then failure/billing behavior. No redundant padding; the only minor inefficiency is the long platform list, which is nonetheless informative.

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?

No output schema exists, but for a three-parameter tool the description covers what the call does, its input precondition, and its billing consequence, which is what an agent needs to decide and call correctly. It could do slightly more on output shape (e.g., whether the transcript is inline or a link), but this is a minor gap.

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 100%, with the format enum and language auto-detect behavior fully documented inline, so the baseline of 3 applies. The description reinforces the 'public' constraint on the url parameter but adds no format or syntax detail beyond the schema.

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?

Uses a specific verb ('Transcribes') with an explicit resource (a public video URL), enumerates the supported platforms, and states what is returned ('the transcript'). It does not differentiate itself from siblings such as get_transcript, so it falls short of a 5, but the operation is unmistakable.

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?

Gives clear operating context: the video must be public, private/restricted videos fail, and the call consumes FastScribe credits with a pointer to get_pricing_and_limits. It does not say when to prefer this over get_transcript/list_transcripts (e.g., fresh URL vs. previously transcribed content), so an agent must infer the boundary.

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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