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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds that the analysis is of 'current' (当前) cross-platform rankings and mentions the resonance score, which is a behavioral detail beyond the annotations. However, it does not disclose any potential limitations or side effects beyond what annotations cover, so it does not add substantial behavioral context.

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?

Two sentences with no redundancy. The core purpose and output are front-loaded, and every word contributes to understanding. It is efficient and well-structured.

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 tool with a simple parameter set, the description explains what it returns (per-platform hits, best ranking, resonance score) and its purpose. It is complete enough for an agent to call it correctly, though it does not specify which platforms are available (likely covered by list_platforms) or any edge cases.

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% with both keyword and platforms described. The description does not add extra meaning beyond the schema, such as format or constraints, so it stays at the baseline for high schema coverage.

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 clearly states the tool's function: analyzing a keyword/topic across platforms to determine cross-platform resonance. It specifies the resource (keyword/topic) and the action (analyze how many platforms it ranks on simultaneously), and it distinguishes from siblings like keyword_trend_curve (single-platform trend) and get_trending (generic trending) by focusing on cross-platform resonance and its output (per-platform hits, best ranking, resonance score).

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 provides a clear use case: to judge if a topic has nationwide heat, which implies when to use it (when cross-platform visibility matters). However, it does not explicitly mention alternatives or when not to use it, though the purpose and the sibling list make the distinction reasonably inferable.

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