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

Beyond the annotations (readOnly, openWorld, idempotent), the description explains the sophisticated behavior: the SEC EDGAR + XBRL fast path vs grounded pipeline, the meaning of each verdict, the critical distinction between could_not_verify (check did not happen) and unsupported (no source), and the return format with citations. This is exactly the kind of behavioral context that helps an agent interpret results safely.

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 long but information-dense, front-loaded with trigger phrases and a clear 'when to use' statement. Each sentence carries meaningful info, from routing logic to verdict definitions to the important error-handling caveat. It could be trimmed slightly, but the structure is logical and scannable.

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 having no output schema, the description enumerates all possible verdicts and their meanings, explains the return payload (value with citation and reasoning), and covers error conditions. It also explains the two-routing paths. This is a complete description for a tool of this complexity, especially with rich annotations.

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?

The input schema fully documents both parameters with descriptions (100% coverage). The description adds some context about tolerance ('exact percent-delta math' and default cap at 5) but does not substantially enhance parameter understanding beyond the schema. Thus baseline 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 immediately identifies the tool as 'natural-language claim verification against authoritative sources' with trigger phrases like 'is it true that…' and 'fact check', clearly distinguishing it from generic Q&A tools. It specifies two pathways (structured SEC for company-financial claims, grounded pipeline for all else) and the returned verdict types, making the 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 says 'Use whenever the agent needs to check whether something a user said is factually correct' and describes the routing behavior, but it does not explicitly name alternative tools or state when not to use this tool. The 'Replaces 4–6 sequential calls' note implies efficiency but not an exclusion, so the guidance is clear but not fully exhaustive.

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