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

With no annotations, the description carries the full behavioral burden. It does disclose the important 'one query per call' scope constraint, but says nothing about auth/API key requirements, rate limits, or failure behavior for invalid video IDs. Return values are covered by the output schema, so that gap is excused.

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?

Purpose is front-loaded in the first sentence, with the scope constraint and CLI alternative following. Every sentence earns its place, though the CLI command snippet is slightly bulky for a tool description.

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 single-parameter read tool with a full output schema and 100% schema description coverage, the description is nearly complete. It covers what is returned, the call-scope constraint, and the batch alternative; only peripheral details like auth requirements are absent.

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?

Only one parameter, and its schema description fully documents the expected video ID format with an example ('rfscVS0vtbw'). Schema coverage is 100%, so the schema does the work and the description needs to add nothing; baseline 4 applies.

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 ('Fetch') and resource ('structured metadata for a YouTube video') and enumerates the returned fields (title, description, views, likes, channel info, technical details). An agent can distinguish it from get_youtube_search_results and get_youtube_video_subtitles without opening any 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?

Explicitly scopes the tool to one query per call and routes batch/disk-output use cases to the ScrapingBee CLI with a concrete command example. It stops short of pointing to the sibling MCP tools (e.g., get_youtube_search_results) that cover adjacent intents, so it is clear context rather than full when/when-not/alternatives guidance.

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