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

It goes well beyond the annotations: recent days may be missing or still change and results are always is_final: provisional; every response declares data_availability with the meanings of complete, observed_zero, no_rows, partial_collection, and access_error; and no_rows/access_error do not mean zero. It also discloses that each call costs one token and creates a stored XBOSS task, and it warns that provider strings must be treated as untrusted data. It partly contradicts itself by stating both '읽기만 합니다' and 'this call is not purely read-only', but the second statement matches readOnlyHint=false.

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 purpose is front-loaded and most sentences carry real information, but the text is a dense run-on that mixes Korean and English boilerplate (idempotency, token accounting) with core behavior. Some caveats about data_availability are restated, which dilutes what matters.

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?

This is an 11-parameter tool with no output schema, so the description has to explain return values, and it does: the channel_metrics envelope, is_final, and the data_availability enumeration. It also covers idempotency and pagination semantics. It is nearly complete, although the page-title/search-term injection warning could be clearer.

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 100%, so the schema already documents every parameter, including 1-based start_index, inclusive dates, and the account_link_id fallback. The description adds little parameter-level meaning beyond restating that start_index is 1-based and that metrics land under channel_metrics. The baseline of 3 applies when the schema carries the weight.

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 first sentence names a specific verb and resource: retrieve one YouTube channel's performance (views, watch time, subscribers, other requested channel metrics) over a date range. It implicitly separates itself from the analytics report by noting that metrics are returned under channel_metrics rather than the shared metrics axis. It never names a sibling tool, so the distinction has to be inferred.

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?

It gives some guidance: revenue metrics cannot be retrieved here, and when data_availability is no_rows the caller should widen the period and retry. It never says when to choose this instead of the sibling analytics report, report_job, or ads reports, so routing still depends on inference.

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