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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses pricing ($0.002 per video scraped) and the shape of the return (video and channel objects), but says nothing about auth requirements, rate limits, quota limits, or error behavior for a paid third-party scraping service.

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 short sentences, front-loaded with the action and the returned fields, then usage context and cost. Every sentence carries information; nothing is padded.

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 4-parameter read-only scraper with no output schema, the definition covers what it fetches, when to use it, its return type, and its cost. Remaining gaps (auth, rate limits, behavior when combining searchQueries with explicit URLs) are modest given the rich schema coverage.

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%, so all four parameters (videoUrls, channelUrls, searchQueries, maxResults) are already fully documented, including accepted URL formats and the 1-50 range. The description adds no parameter-level detail beyond it, making the baseline 3 appropriate.

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 (scrape) and resource (YouTube videos and channels) and enumerates the data returned (views, subscribers, metadata, descriptions). The platform-specific framing cleanly distinguishes it from the platform siblings like tiktok_scraper and instagram_scraper.

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?

'Use when researching content trends, analyzing creators or building YouTube datasets' gives clear contextual triggers for selection. It does not name exclusions or say when a sibling scraper would be preferred, so it falls short of a 5.

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