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

Beyond the annotations (read-only, idempotent, open-world), the description discloses crucial behavioral details: the meaning of each verdict, especially the 'could_not_verify' error distinction with verification_error{stage,detail}, and the definition of 'unsupported'. It also explains the fast-path vs. grounded routing logic and that output includes verbatim evidence and citations—any significant behavioral traits.

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 typical but is front-loaded with usage and covers important edge cases. It is logically structured from examples to return behavior to caveats; every sentence adds value, though a slight trim could improve conciseness without losing information.

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 explains return values (verdict types, actual value with citation, reasoning) and defines ambiguous terms (could_not_verify, unsupported). It also covers the two distinct code paths and the tolerance semantics, making it complete for a tool of this complexity.

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 coverage is 100% and both parameters already have clear descriptions in the input schema. The tool description adds minor tactical guidance (e.g., setting tolerance_pct to 1–2 for hallucination detection) but does not materially extend beyond what the schema provides; the baseline of 3 is appropriate.

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 clearly states a specific verb (validate) and resource (natural-language claim), with example query forms and an explicit statement that it check factual correctness. It also distinguishes itself from siblings by noting it replaces 4–6 sequential calls and covers both structured financial and grounded fallback paths.

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 says 'Use whenever the agent needs to check whether something a user said is factually correct.' It also delineates when the fast path applies (company-financial claims) vs. the fallback (any other factual claim), and notes it replaces multiple sequential calls, guiding when to invoke this tool instead of composing a pipeline.

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