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

Annotations already declare readOnly/idempotent/non-destructive behavior, satisfying the safety profile. The description goes further by explaining failure semantics: could_not_verify means the check did not happen and carries verification_error, unsupported means no source covers the claim, and both must be interpreted differently from confirmed/refuted. No contradiction with 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 information-dense; every sentence contributes (examples, routing logic, return structure, failure modes, efficiency). It is front-loaded with query patterns and follows a logical outline, though it could be tightened without losing value.

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?

There is no output schema, but the description compensates by enumerating the verdict values, stating the return includes the actual value with pipeworx:// citation and reasoning, and detailing error handling for could_not_verify. This gives enough context for an agent to invoke the tool and interpret results 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?

Input schema has 100% description coverage, so the baseline is 3. The description adds meaningful nuance for tolerance_pct, explaining it overrides the claim-wording-implied tolerance and recommending 1–2% for hallucination detection. This goes beyond the schema's simple type/range description.

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 opens with natural-language query patterns ('Is it true that…' / 'fact check') and clearly states the core function: natural-language claim verification against authoritative sources. It differentiates from siblings by noting it replaces 4–6 sequential calls and by routing company-financial claims vs. other claims to different pipelines.

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?

It explicitly says 'Use whenever the agent needs to check whether something a user said is factually correct.' It also gives concrete guidance on when the structured SEC EDGAR path is used versus the grounded pipeline, and clarifies the important distinction between could_not_verify and unsupported verdicts, helping callers avoid misusing results.

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