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

The description discloses the exact success response shape, the full refusal_reason enum, and the grounded-extraction behavior, all beyond what the annotations provide. It also notes the extra LLM call cost and that refusals occur when data doesn't directly answer. This does not contradict the readOnly, idempotent, or non-destructive 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 information-dense and front-loaded, leading with the core purpose and then the critical behavioral contract. Every sentence contributes: routing explanation, response shape, refusal conditions, use cases, and cost tradeoff. There is no filler or repetition.

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?

With no output schema, the description supplies the full return contract including evidence, confidence, source, and refusal reasons. Annotations cover the safety profile, the schema covers the input parameter, and the description covers usage and behavior, leaving no material gap for an agent to invoke this 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?

Schema description coverage is 100%, with the question parameter fully documented and aliases enumerated. The description adds context about the question being routed and grounded, but no additional parameter-level semantics are necessary given the schema already covers them.

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 this is a hallucination-resistant answer mode for high-stakes reads and explains that it extracts answers only from what the tool result contains. It explicitly contrasts itself with ask_pipeworx, distinguishing this grounded mode from the standard routing variant despite similar names.

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 gives explicit when-to-use guidance: whenever an answer will be quoted, cited, or acted on and facts must not be invented, with concrete examples like financial, legal, medical, or public-statement contexts. It also names the alternative and preference rule: prefer ask_pipeworx for casual lookups because this mode costs one extra LLM call.

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