transcript_textFetch any YouTube video transcript as plain text (free, no AI).
Raw captions with timestamps, nothing else. For a formatted file use transcript_markdown; for AI summaries use get_video_intelligence. Free, no payment required.
| Name | Required | Description | Default |
|---|---|---|---|
| video_url | No | YouTube video URL or video ID |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Input schema / properties / x_paymentRemoved value: -{
- "default": "",
- "description": "Base64 x402 payment payload (required — pass the X-PAYMENT value as an argument over MCP)",
- "type": "string"
-}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, non-destructive, open-world. The description adds non-annotation context: it is free/no AI, returns raw captions with timestamps and 'nothing else'. It doesn't discuss failure modes (no captions, private video) or rate limits, so it falls short of 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with the core capability and the two alternatives; every sentence carries routing information. Minor redundancy: 'free, no AI' is restated as 'Free, no payment required' at the end.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values need not be explained, and the description covers capability, cost, output character, and sibling routing. Nothing an agent needs to invoke it correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the single parameter is fully documented as 'YouTube video URL or video ID'. The description's 'any YouTube video' adds no syntax or format detail beyond that, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb+resource+format: 'Fetch any YouTube video transcript as plain text.' It immediately distinguishes itself from two named siblings, so an agent can tell what it returns 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.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit routing: transcript_markdown for a formatted file, get_video_intelligence for AI summaries. This is exactly the when-to-use-this-vs-alternatives guidance the dimension asks for.
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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