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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false. The description adds meaningful behavioral context beyond those annotations: the 2-credit cost, the free-credit note, and the conditional 'when available' behavior for keyword clusters from TikTok Analytics.

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-loaded with the core action and resource. Cost and usage guidance each earn their place. The first sentence is slightly overstuffed and 'audience sentiment/audience-signal analysis' is somewhat redundant, preventing a perfect score.

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 read-only, two-parameter fetch tool with an output schema, the description covers purpose, platforms, cost, and alternative routing. It could be slightly more complete about behavior like pagination or output shape, but the output schema and limit parameter mitigate those gaps.

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%: both 'url' and 'limit' are already well documented in the schema, including the default of 20. The description adds platform context but does not meaningfully expand on parameter format, range, or constraints beyond what the schema provides.

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 uses a specific verb ('Fetch'), a clear resource ('top comments for a post URL'), and enumerates all supported platforms. It also distinguishes itself from analyze_comments and other siblings by describing the additional keyword cluster output.

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 explicitly states when to use this tool ('when you want to read what people actually wrote') and when to use the alternative ('use analyze_comments when you want it synthesised into what to do next'). This gives an agent a clear selection rule.

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