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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds value by disclosing the response envelope including an `errors` field, signalling partial-failure behavior across platforms. It does not mention freshness/latency or rate limits, which would push it to a 5.

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 labeled clauses (purpose / when to use / do not use / returns) with zero filler and the purpose front-loaded. 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?

No output schema exists, but the description supplies the return shape inline ({platform, count, items:[{title, heat, url, source}], errors}). Combined with the top-level selection guidance and platform coverage, an agent has everything needed to call it correctly.

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 the burden — it names the platforms (mapping to the enum) but says nothing about `limit` (range 1-30, default 10) or what `platform: all` aggregates. Partial compensation for two undocumented parameters.

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 verb+resource ("cross-platform social hot lists") and enumerates the exact platforms covered. An agent can immediately tell this apart from attention_trend and web_search without opening any schema.

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?

Explicitly names when to use it ("what people are talking about now, content ideas, trend discovery") and when not to, routing to two named alternatives (attention_trend for search interest over time, web_search for general web search). Nothing is left to inference.

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