transcribe_youtube
YouTube video -> structured transcript + timestamped summary. $0.10/call via x402.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| format | No | both |
YouTube video -> structured transcript + timestamped summary. $0.10/call via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| format | No | both |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden of behavioral disclosure. It does mention a cost ('$0.10/call via x402') and the output format ('structured transcript + timestamped summary'), which are useful. However, it omits details about potential side effects, rate limits, error conditions (e.g., video unavailable), or authentication requirements, leaving gaps given the absence of annotations.
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?
The description is a single, front-loaded sentence that efficiently conveys the tool's primary function and a key cost detail. There is no wasted verbiage, and the structure is clear and scannable.
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?
Given the tool has two parameters, no output schema, and no annotations, the description is too thin to be fully effective. It omits critical context such as what the 'format' parameter does, possible output structures, and any limitations or prerequisites. While the basic purpose is clear, the missing parameter semantics and absence of behavioral details leave the description incomplete for an agent to confidently invoke the tool correctly.
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?
The input schema has two parameters (url and format) with no descriptions, and schema description coverage is 0%. The description mentions 'YouTube video' (implicitly the url) and 'transcript + timestamped summary' (likely related to format), but it fails to explain the 'format' parameter's allowed values or behavior. The url parameter is at least somewhat inferred, but format remains ambiguous, so the description does not adequately compensate for the schema's lack of detail.
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?
The description clearly states the core function: 'YouTube video -> structured transcript + timestamped summary.' This specifies the resource (YouTube video) and the output (transcript and summary), making it distinct from sibling tools like web_read or extract_pdf. The arrow effectively conveys the transformation, and the tool name reinforces the verb.
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?
The description implies usage for transcribing YouTube videos, but it doesn't explicitly state when to use this tool vs alternatives (e.g., web_read for non-transcription web content). It also doesn't mention exclusions or prerequisites like video length limits or age restrictions. The guidance is solely implicit through the purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: company lookup, crypto price, email verification, PDF extraction, KDP data, social profile lookup, YouTube transcription, and web reading. No two tools overlap in their primary function, so an agent can easily select the right one.
Names follow a snake_case convention but mix verb-object (extract_pdf, transcribe_youtube) and object-verb (company_lookup, email_verify, web_read) orders. Also, crypto_price is noun-noun, breaking the verb pattern. The inconsistency is noticeable but names remain readable.
With 8 tools, the server is well-scoped for a general-purpose utility API. Each tool adds a distinct capability without redundancy or bloat, fitting comfortably within the optimal 3-15 tool range.
The set covers common agent needs like web reading, PDF extraction, email verification, and social/company analysis. However, some obvious utilities like image processing or file conversion are absent, representing minor gaps but not severe dead ends.