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

Annotations already indicate read-only, idempotent, open-world, non-destructive behavior, and the description adds substantial context beyond that: the SEC EDGAR fast path, the grounded pipeline, verbatim evidence, and especially the critical caveat that could_not_verify means the check did not happen and must not be treated as evidence. This is exactly the kind of behavioral nuance agents need.

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 average but every sentence earns its place: trigger phrases, when-to-use, routing, return value, and error semantics. It is front-loaded with purpose and structured logically. Slightly dense, but not wasteful.

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 no output schema, the description fully explains the return verdicts, the actual value with citation, reasoning, and the meaningful distinction between could_not_verify and unsupported. It covers the tool's complexity and edge cases thoroughly, making it self-sufficient for an agent.

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 the schema already describes both parameters well. The description adds extra meaning for tolerance_pct by explaining it overrides the claim-wording implied tolerance and recommending 1–2 for hallucination detection. This exceeds the baseline 3 for fully covered schemas.

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 states a specific verb (verify/check) against a clear resource (natural-language factual claims) and enumerates trigger phrases. It also distinguishes company-financial claims (SEC EDGAR/XBRL fast path) from all other factual claims, which differentiates it from sibling research/ask 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?

Explicitly says 'Use whenever the agent needs to check whether something a user said is factually correct.' It also describes the routing behavior for company-financial vs. other claims and mentions it replaces 4–6 sequential calls. However, it does not name specific alternative tools or state when not to use it, so it stops short of a full 5.

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