verify_claim

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

No annotations are provided, so the description carries the full burden, and it does disclose the return payload (conclusion, official site/repo/media evidence, copycat-site warning, fully sourced write-up) plus a concrete operational limit of at most 4 searches per item. It stops short of stating failure behavior, latency, or that the tool is read-only, which keeps it from 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 dense sentences: purpose first, then what is returned, then the search budget. Every sentence earns its place, though the facet list slightly repeats the overall intent (是否发布 echoes the verb 查证).

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?

With no output schema and no annotations, the description must describe both behavior and returns, and it does: it lists the conclusion, evidence types, copycat-site warning, and sourced article, plus the search limit. Missing are failure modes and confirmation that only AI product claims are in scope, but nothing critical to calling it correctly is absent.

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?

The single `claim` parameter has 0% schema description coverage, so the schema adds nothing. The description partially compensates by indicating a claim should be an AI product item with attributes like release date, open-source status, and publisher, but it gives no guidance on required phrasing, granularity, or whether one call covers one facet or all of them.

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 names a specific verb (查证/verify) and a specific resource (一条 AI 产品消息), then enumerates the exact facets checked: release date, open-source status, publisher, and whether it shipped. It does not explicitly distinguish itself from the sibling verify_digest, leaving a small ambiguity about which verifier to pick, but the scope is otherwise unambiguous.

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?

Usage is implied by the description: use it for a single AI product news item, with a stated cap of 4 Yuanbao searches per item. However, it never says when to prefer verify_digest over verify_claim or what to do for non-AI-product claims, so the routing decision 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.