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

With annotations already declaring read-only, open-world, and idempotent behavior, the description adds significant context beyond annotations: it explains the routing logic, the verdict list, and critically distinguishes 'could_not_verify' (check didn't happen) from 'unsupported' (no source exists). It also warns callers not to treat 'could_not_verify' as evidence, which is a key behavioral nuance.

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 lengthy but information-dense, with trigger phrases front-loaded and structured progression from behavior to return value to caveats. Every sentence contributes, though some could be tightened; the efficiency of the '4–6 sequential calls' note adds value without excessive verbosity.

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?

Given the tool's complexity (routing, multiple verdicts, error cases) and absence of an output schema, the description is remarkably complete. It explains what is returned (verdict, value with citation, reasoning), clarifies the distinction between 'could_not_verify' and 'unsupported', and even notes the performance benefit. Minor omissions like confidence scores do not hinder usability.

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%, so the baseline is 3. The description enriches parameter understanding by explaining how tolerance_pct overrides the claim's implied tolerance and suggesting set 1–2 for hallucination detection. It also ties the claim format to the SEC EDGAR math, adding value beyond the schema.

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: natural-language claim verification with specific trigger phrases like 'fact check' and 'verify the claim'. It distinguishes itself by describing the SEC EDGAR fast path and fallback grounded pipeline, and explicitly notes it replaces 4–6 sequential calls, setting it apart from potential alternatives.

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 clear guidance on when to use the tool: 'Use whenever the agent needs to check whether something a user said is factually correct.' It also differentiates claim types (company-financial vs. other) but does not explicitly state when not to use it or name alternative tools, leaving some room for ambiguity.

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