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

Goes well beyond the sparse annotations: describes hybrid keyword+vector retrieval with RRF fusion, claimed-person ranking, cloud-user behavior (only send_cooperation_request, not start_conversation), and the server-side guarantee that phone-number queries always return empty. These are real behavioral constraints an agent needs to know.

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 long but tightly structured with labeled sections (何时用, 机制, 云用户, 组合链, 常见 pitfall), and every section earns its place. The most important usage guidance is front-loaded, and nothing reads as filler.

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?

Despite having no output schema, the description lists the result fields (canOffer / similarity / claimed / isCloud), explains cloud-user edge cases, covers unsupported phone-number search, and routes to downstream tools. An agent has enough context to decide when to call it and what to do with results.

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%, and both q and limit are already well documented in the input schema. The tool description reinforces that q should be a natural-language expression of what the user wants the other person to offer, but it does not add substantially new parameter-level semantics.

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 opens with concrete when-to-use examples and defines the search target precisely: people/主理人 by what they offer (canOffer), plus nickname/bio/identity tags. It explicitly distinguishes itself from search_products and search_needs, and the title aligns with the tool's actual behavior.

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?

Provides explicit when-to-use guidance with real user-intent examples, names sibling alternatives for products and needs, and gives a follow-up action chain (get_creator → start_conversation / contact_need). It also warns about the phone-number pitfall and tells the agent how to respond, which is unusually actionable.

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