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

Annotations already provide readOnly/idempotent hints, but the description adds rich behavioral detail: the dual pipeline (SEC EDGAR fast path vs grounded fallback), the precise meaning of each verdict, and a critical warning that could_not_verify means the check did not happen and must not be treated as evidence. This goes well beyond what annotations convey.

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?

Though long, every sentence earns its place: it includes invocation examples, pipeline routing, verdict definitions, caller instructions, and a clear 'IMPORTANT for callers' note. The structure is logical and front-loaded with the core purpose, making the length justified.

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?

For a tool with no output schema, the description is remarkably complete. It explains inputs, internal processing paths, return values, edge cases (could_not_verify vs unsupported), and even advises on how to interpret each verdict. There are no significant gaps for an agent to invoke and use it correctly.

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% (both parameters have descriptions), but the description adds extra practical guidance on tolerance_pct—e.g., setting 1-2 for hallucination detection and explaining the default behavior—plus illustrative claim examples. This adds value beyond the schema, though the schema already does most of the heavy lifting.

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 the tool's purpose with a specific verb+resource: natural-language claim verification against authoritative sources. It distinguishes itself from siblings by focusing on fact-checking claims and explicitly mentions replacing 4-6 sequential calls, making its role unique among the listed 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?

The description explicitly says 'Use whenever the agent needs to check whether something a user said is factually correct' and provides clear routing context for company-financial vs other claims. It does not name alternative tools or state when not to use it, but the context is strong enough for a 4.

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