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

Even with readOnlyHint, openWorldHint, and idempotentHint already provided, the description adds crucial behavioral detail: the exact verdict vocabulary, the meaning of could_not_verify (with verification_error and "must not be shown as one"), and the distinction between unsupported and could_not_verify. It also discloses the routing behavior and citation format, going well beyond the annotations.

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 longer than average, but the opening query phrases immediately signal scope, followed by the purpose and key routing logic. The later error-semantics paragraph is essential and not redundant. A slight trim of the "grounded pipeline…then judged" phrasing could tighten it, but it remains well organized.

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, the description fully compensates by enumerating the returned verdict types, the evidence/citation, reasoning, and the error payload for could_not_verify. It also covers both input parameters and explains what unsupported vs could_not_verify mean. For a tool of this complexity, the description is complete.

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?

Although schema coverage is 100%, the description enriches both parameters. It explains that tolerance_pct overrides the claim-wording default, is capped at 5, and recommends 1–2 for hallucination detection. It also gives realistic claim examples, so the caller understands what a valid claim looks like.

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 natural-language triggers ("Is it true that…", "fact check", "verify the claim that…") and explicitly states the tool's job: natural-language claim verification against authoritative sources. It distinguishes the structured SEC EDGAR path for company-financial claims from the grounded pipeline for all other factual claims, which separates it from sibling research or AI-visibility tools.

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?

It gives clear usage direction: "Use whenever the agent needs to check whether something a user said is factually correct." It also explains that company-financial claims take the structured path and all other claims fall through to the grounded pipeline, and states the tool replaces multiple sequential calls. It does not explicitly name when-not-to-use alternatives, but the guidance is unambiguous for the core use case.

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