Fetch the raw transcript text of a YouTube video (no model run — the cheaper SKU), in any of 100+ languages (language param, BCP-47). Pay-per-call via x402 (USDC on Base), no account. A video without captions returns an error and is not charged.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| language | No | en |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses key behaviors: no model run (cheaper), pay-per-call via x402, no account needed, and no charge on error. It could additionally mention the output format (raw text), but is largely transparent.
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?
Three sentences, front-loaded with the primary purpose, then payment details, then error handling. No wasted words, each sentence adds distinct value.
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 2-parameter tool with no output schema, the description covers purpose, parameters, error handling, and pricing. Missing explicit output format detail (e.g., raw plain text) but is largely complete.
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 coverage is 0%, so the description adds meaning: url is the video link, language is BCP-47 with default 'en', supporting 100+ languages. This compensates for the lack of schema descriptions.
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 tool fetches raw transcript text of a YouTube video and explicitly notes it is the 'cheaper SKU' without a model run, distinguishing it from sibling tools like summarize_youtube_video.
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 explains when to use (fetching transcript, cheaper option) and mentions error handling (no captions returns error without charge). It implicitly differentiates from siblings but does not explicitly state when not to use it.
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 distinct purpose: fetching transcripts, listing new channel videos, and summarizing videos. The descriptions clearly differentiate them with no overlap in functionality.
All tool names follow a consistent verb_noun pattern: get_youtube_transcript, list_new_channel_videos, summarize_youtube_video. No mixing of conventions.
Three tools cover the core capabilities needed for a video summarizer: transcript retrieval, channel monitoring, and summarization. The count is well-scoped and not excessive.
The tool set fully covers the stated purpose: obtaining transcript data, monitoring for new videos, and generating summaries. No obvious gaps for the intended use case.
