Full plain-text transcript of a YouTube video, de-duplicated and cleaned from the captions. Accepts a video id or URL. Ideal for feeding video content to LLMs. JSON response. [Paid: $0.01 USDC per call via x402 on Base; the calling client pays automatically.]
| Name | Required | Description | Default |
|---|---|---|---|
| v | Yes | YouTube video id or full URL |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description partially carries the burden: it discloses deduplication, cleaning, JSON response, and payment cost ($0.01 USDC per call). However, it omits error handling, rate limits, or what happens if captions are unavailable.
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 concise: two main sentences plus a brief payment note. It is front-loaded with the core purpose and avoids redundancy, though the payment info could be integrated more smoothly.
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?
For a simple tool with one parameter and no output schema, the description covers purpose, input format, output format (JSON), and cost. It lacks error scenarios but is sufficient for typical use.
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 description merely repeats the schema's parameter note ('Accepts a video id or URL'), adding no additional semantic value.
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 specifies the tool's function: extracting a full plain-text transcript from YouTube videos, with details on deduplication and cleaning. It uniquely distinguishes itself from sibling tools like 'pdf-extract' or 'reader' by targeting video content.
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 suggests use for feeding video content to LLMs, providing a clear context. However, it does not explicitly state when not to use this tool or mention alternatives among siblings.
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 of the 30 tools has a highly specific, non-overlapping purpose, from brand visibility to chemical safety to YouTube transcripts. Descriptions are detailed and clearly differentiate each tool's function, eliminating ambiguity.
All tool names use lowercase with hyphens, creating a consistent visual pattern. However, the structure varies: some are noun-verb (email-validate, pdf-extract), others noun-noun (brand-visibility, chem-compat). This minor inconsistency prevents a perfect score.
With 30 tools, the server offers a very broad surface. While each tool earns its place as a distinct utility, the high count may overwhelm agents and dilute focus. It is borderline heavy for a single server, hence a score of 3.
The tool set covers a wide range of domains: business, chemicals, crypto, domain, email, finance, holidays, trade, jobs, legal, mapping, medical, news, packages, electronics, PDF, product, recall, sanctions, screenshots, SEC, tech stack, web archive, web search, YouTube. Yet it lacks some common utilities like weather, translation, or image analysis, leaving notable gaps for a general-purpose utility server.