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

Beyond the readOnly/idempotent annotations, it discloses non-obvious behavior: the six possible verdicts, that could_not_verify means the check did not happen and carries verification_error{stage,detail}, and that unsupported means no covered source exists. The 'IMPORTANT for callers' caveat directly prevents a dangerous misinterpretation.

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 the length is justified by trigger phrases, dual routing paths, verdict semantics, and caller caveats. It is front-loaded with the purpose and organized into clearly scoped sections; only the list of synonymous query phrasings is slightly repetitive.

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 enumerates the return shape (verdict, actual value with pipeworx:// citation, and reasoning) and error semantics. It also explains both internal verification paths and what each non-obvious verdict means, leaving no critical operational gap for callers.

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 already documents both parameters at 100% coverage, including tolerance_pct range and override semantics, so the description does not need to repeat them. The description adds context about exact percent-delta math for financial claims, but no additional parameter-level meaning 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 names the exact capability: natural-language claim verification and fact-checking, with explicit trigger phrasings and a clear distinction from generic Q&A. It specifies the verification methods (SEC EDGAR/XBRL fast path vs grounded pipeline) and a defined verdict set, so an agent can separate it from siblings like ask_pipeworx or deep_research.

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?

States a direct when-to-use rule: 'Use whenever the agent needs to check whether something a user said is factually correct,' and further splits company-financial claims from other factual claims. It does not explicitly name sibling tools to avoid, so it misses the full 5-level 'when-not/alternatives' criterion.

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