YouTube Video Summarizer (pay-per-call)

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.

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

With no annotations provided, the description carries full burden. It discloses pay-per-call via x402, no account/API key, and that unresolved channels or naive timestamps return errors without charge. This provides critical behavioral context beyond basic functionality.

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, well-structured paragraph that front-loads the purpose and efficiently covers usage, return values, pricing, and error handling. Every sentence adds value with no wasted words.

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 no output schema, the description explains return fields (new videos ids/titles/times) and pagination cursor. It addresses pricing and error states, making it complete for a tool of this complexity without needing additional context.

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 description compensates by explaining the three parameters: channel (required), since (ISO 8601 timestamp), and since_video_id (optional cursor). It clarifies their usage and mentions the output new_video_id for pagination, adding meaning beyond the bare schema.

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 lists new videos on a YouTube channel since last poll, with a specific verb ('list') and resource ('new channel videos'). It distinguishes from sibling tools like get_youtube_transcript and summarize_youtube_video, which serve different functions.

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 the tool (pass channel URL/@handle/id, optional cursor) and how to paginate with new_video_id. It notes error conditions and pricing but lacks explicit alternatives or when-not-to-use guidance, though siblings are clearly different.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries full burden. It discloses pay-per-call via x402, no account/API key needed, error handling (no charge for failures), and language support. It omits idempotency or caching behavior, but the key behavioral traits are covered.

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 (4 sentences), front-loaded with the primary purpose, and each sentence adds unique value: summarization action, payment model, cost comparison, and error handling. No redundant or extraneous content.

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's simplicity (2 params, no output schema), the description covers payment, error handling, language support, and differentiation from siblings. Missing details about return format (e.g., plain text or structured) and synchronous nature, but overall reasonably complete for agent usage.

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 0%, so the description must add meaning. It explains that language uses BCP-47 format and supports 100+ languages, and implies url is a YouTube video URL. However, it does not specify whether url should be full URL or just video ID, leaving ambiguity. The description partially 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 summarizes a YouTube video using Claude and returns summary text in multiple languages, distinguishing it from sibling tools like get_youtube_transcript (which returns raw transcript) and list_new_channel_videos (listing metadata).

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 provides context on when to use this tool: it's cheaper than fetching a transcript separately, and it highlights failure cases (bad URL or no captions) that result in no charge. However, it does not explicitly list scenarios where alternatives would be better (e.g., if full control over summarization or offline processing is needed).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.