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

Annotations already convey readOnly/idempotent/non-destructive hints, and the description adds substantial behavioral context beyond that: the extraction-only-verbatim rule, the explicit refusal contract with enumerated refusal_reason values, and the one-extra-LLM-call cost. It also clarifies that the tool may refuse when the data doesn't directly answer, which is critical for high-stakes use.

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?

Every sentence earns its place: the first front-loads the core behavior, the second details the contract and return shape, and the third gives usage and trade-off guidance. Despite being information-dense, there is no filler or redundancy.

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?

For a tool with no output schema, the description explains the full return structure and refusal reasons, covers the cost difference, names the alternative, and specifies the reliability context. It gives an agent everything needed to call it correctly and interpret results.

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 provides 100% coverage, including a clear description of the question parameter and alias relationships. The description adds only that the question is in 'natural language,' which the schema already states. It does not substantially enrich parameter semantics beyond the schema baseline.

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 clear, specific verb and resource: it is a 'hallucination-resistant answer mode' that extracts answers using only the tool result, with a distinct refusal mechanism. It explicitly contrasts itself with the sibling ask_pipeworx ('Same routing as ask_pipeworx... then EXTRACTS the answer'), making the differentiation immediate and unambiguous.

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 gives explicit when-to-use guidance: 'Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts' and provides a concrete alternative with a cost trade-off: 'Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups.' This fully directs selection among siblings.

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