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

Annotations already signal read-only, idempotent, and non-destructive behavior, so the description adds high-value semantics: it enumerates the six verdicts and crucially explains that 'could_not_verify' is a failure state, not evidence, and 'unsupported' means no source was found. This prevents callers from misinterpreting results, going well beyond structured 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 lengthy but well-organized: it opens with the tool's core purpose and usage, then details return values and critical caveats. The 'replaces 4–6 sequential calls' note is slightly ancillary but still useful for understanding value. Every major sentence carries necessary information, though it could be tightened.

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?

Despite lacking an output schema, the description fully specifies what the tool returns (verdict, actual value, citation, reasoning) and clarifies ambiguous outcomes (could_not_verify vs. unsupported). It also describes the two routing paths and error conditions, making it complete for an agent to decide when and how to invoke the tool.

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 both parameters are already documented. The description adds meaningful context for tolerance_pct by explaining it overrides the claim's implied tolerance and is intended for hallucination detection (1–2%), and it frames the claim parameter with realistic examples. This elevates it above the baseline 3.

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 identifies validate_claim as a natural-language claim verification tool against authoritative sources, with specific trigger phrases and two execution paths (SEC EDGAR fast path vs. grounded pipeline). It distinguishes itself from sibling tools by positioning it as a single call that replaces 4–6 sequential steps, making its purpose unambiguous.

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 states 'Use whenever the agent needs to check whether something a user said is factually correct,' giving a clear when-to-use rule. It also explains internal routing for company-financial vs. other claims, providing useful context. However, it does not name alternative tools or state when not to use it, so it lacks explicit exclusions.

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