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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the bar is lower, and the description still adds real context: ranking is by 'latest dated public views' and 'Views are sampled-video observations, not channel totals', which prevents a serious misinterpretation of the numbers.

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 front-loaded sentences with almost no filler; the ranking criterion and the sampling caveat are stated before detail. The enumeration of return fields is slightly redundant given an output schema exists, but it is compact.

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?

Return values are effectively covered (output schema exists and the description previews fields), and the sampling caveat is a strong addition. Gaps remain around the limit parameter and when this tool beats search_ai_monks or winning_playbooks.

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 carry parameter meaning. It clarifies that account_id is optional but says nothing about the limit parameter's purpose, default of 10, or maximum of 50, leaving half the params undocumented anywhere.

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 resource (AI monk video samples) and a clear ranking criterion (latest dated public views), plus the payload fields returned. It is distinguishable from siblings like search_ai_monks and winning_playbooks by its ranking/observation framing, though it never explicitly contrasts with them.

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?

There is no when-to-use or when-not-to-use guidance and no named alternative among the five siblings. The only routing hint is 'Optional account_id', which implies a global-vs-account-scoped choice but leaves the agent to infer it.

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