classify_claim

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only states the classification task and that signal basis is produced. It omits whether the tool performs any independent verification, how has_source impacts the classification, and whether there are side effects, limitations, or external dependencies.

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 a single front-loaded sentence immediately followed by compact argument explanations. There is no filler, redundant text, or restatement of the tool name, making it efficient for an agent to parse.

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?

The description covers the core task and parameter meanings, but with no output schema and no annotations, it leaves gaps: it does not specify the exact output format, how the classification result and signal basis are presented, or how has_source influences the categorization. These details are relevant for an agent deciding how to invoke the tool and interpret its response.

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 Args section is critical and it delivers: text is defined as the conclusion text to classify, and has_source is described as indicating whether a source with institution, URL, and date is attached. This provides real semantic meaning beyond the bare schema types and defaults.

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 uses a specific verb, '归类' (classify), with a clear resource, '一条结论' (a claim/conclusion), and enumerates the three output categories: verified fact, reasonable inference, and to-be-verified. This makes the tool's function easy to distinguish from the sibling tools, which all concern different activities like researching companies or drafting outreach, though it does not explicitly name a sibling.

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 provides no guidance on when to use this tool versus alternatives. It only states the operation and arguments, leaving the agent to infer its place in the workflow. No context, exclusions, or alternative routing is provided.

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