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

Beyond the annotations (readOnlyHint=false, destructiveHint=false, openWorldHint=true), the description discloses a meaningful side-effect: each query accumulates local snapshots and bounded history for trend-change and benchmark analysis. This adds behavioral context that the annotations do not fully convey, showing state accumulation without contradicting the non-destructive flag.

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 three sentences with no filler: main purpose, query options with default behavior, and side-effect disclosure. Information is front-loaded, and every sentence earns its place.

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 tool with zero required parameters, no output schema, and all parameter descriptions in the schema, the description covers the essential invocation details: parameter combinations, default case, and side effects. It does not explain return format, but with no output schema and simple optional params, the guidance is sufficient for correct agent invocation.

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%, so the baseline is 3. The description adds value by clarifying the interaction between platform and category, including the comma-separated platform format and the fallback behavior when neither parameter is provided—details not explicit in the schema. This extra semantic guidance justifies a 4.

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 retrieves current hot topic rankings (获取当下热点榜单), identifies the query dimensions (platform/category), and describes the default cross-platform behavior. It does not explicitly differentiate from sibling tools like discover_trending_topics, but the verb and resource are specific enough for basic distinction.

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 explains how to use the tool—by platform, by category, or with neither for cross-platform core rankings—but gives no explicit guidance on when to prefer this tool over alternatives such as discover_trending_topics or take_snapshot. The usage context is implied rather than directly contrasted with siblings.

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