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

Beyond annotations (readOnly, openWorld, idempotent), the description discloses important behavioral details: dual routing based on claim type, the exact set of verdicts, the fact that 'could_not_verify' means the check did not happen and must not be treated as evidence, and that answers include verbatim evidence with pipeworx:// citations. This is rich context that substantially aids correct invocation and interpretation.

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 dense but efficient: it front-loads natural-language triggers, states the core purpose, explains the two paths, lists the output verdicts, and clarifies edge cases. Every sentence adds value; however, it is somewhat long for a tool with only 2 params, though the complexity of the return semantics justifies the length.

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?

Given the absence of an output schema, the description fully explains what the tool returns: verdict, actual value with citation, reasoning. It also covers both the fast path and fallback path, and gives crucial guidance on distinguishing 'could_not_verify' from 'unsupported'. For a 2-param tool, this is complete and self-contained.

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 schema already covers 100% of parameters, but the description adds meaningful semantics for 'tolerance_pct' by explaining that it overrides the claim-wording default, is capped at 5, and can be set to 1-2 for hallucination detection. It also provides concrete claim examples for the 'claim' parameter. This goes beyond the schema's basic descriptions.

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 states the tool's function with specific verbs like 'verify' and 'fact check', identifies the resource as 'natural-language claim verification against authoritative sources', and distinguishes it from sibling tools by mentioning it 'Replaces 4–6 sequential calls'. It also outlines two distinct processing paths (SEC EDGAR for financial claims, grounded pipeline for others), leaving no ambiguity about what the tool does.

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.' It also differentiates when the structured SEC EDGAR path applies versus the general grounded pipeline, and warns about the meaning of 'could_not_verify'. It doesn't name specific alternative tools, but the 'Replaces' framing and clear use-case make the guidance strong.

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