YouTube Video Summarizer (pay-per-call)

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

No annotations, so the description carries the full burden and does so: 1 MB input cap, invalid JSON raises with line and column and is not charged, pay-per-call via x402 (USDC on Base) with no account or API key, and the exact output modes. Error, limit, and cost behavior are all disclosed.

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?

Four dense sentences, each earning its place: purpose first, then parameter semantics, then limits/errors, then the payment model. Zero filler.

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?

No output schema exists, and the description still explains the return value (pretty-printed or minified JSON), plus size limit, failure mode, and billing. Nothing an agent needs to call this 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 coverage is 0%, so the description must supply parameter meaning, and it does: pretty=true means two-space indentation and false minifies; sort_keys sorts object keys alphabetically while leaving array order alone. The required text parameter itself is only implicitly described as the raw JSON input, a minor gap.

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?

States a specific verb and resource: validate raw JSON and return it pretty-printed or minified. An agent knows exactly what this does and what the two output modes are 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?

Clear operational context (input cap, default pretty=true, default sort_keys=false, payment model), so the agent knows how to invoke it. No explicit when-not-to-use guidance, but this is a single-purpose utility with no overlapping sibling to route away from.

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 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 provided, the description carries the full burden of behavioral disclosure. It thoroughly covers pay-per-call via x402 (USDC on Base), no account or API key requirement, error and non-charge behavior for invalid inputs, and the 60-minute length limit. This goes well beyond a simple action statement.

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 compact and front-loads the core purpose, then efficiently conveys critical operational details like payment, auth, error behavior, and length constraints. Every sentence adds distinct value with no filler, making it appropriately dense for a paid API tool.

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 and no annotations, the description is remarkably complete. It covers purpose, output text, language selection, payment model, missing auth requirements, cost rationale, error cases, and length limits—everything an agent needs to decide and execute a call correctly. Schema defaults are rightly left to the schema.

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 no parameter descriptions, so the description must compensate. It adds meaning for the `language` parameter (100+ languages, BCP-47 format) and for `url` by explaining that bad URLs produce errors without charge. It does not fully elaborate on URL formats or the default language, but the schema already provides the default.

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's function: summarize a YouTube video and return the summary text, with a specific verb and resource. It does not explicitly contrast itself with sibling tools like get_youtube_transcript or list_new_channel_videos, so it falls short of a 5, but the action is unambiguous.

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 gives implicit usage guidance by noting it is cheaper than pulling the full transcript into your own context)Skip, and it specifies conditions under which it errors (bad URL, no captions, videos over 60 minutes, undeterminable length). However, it never explicitly states when to prefer sibling tools or what alternatives exist, leaving the guidance implied rather than direct.

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