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

Beyond the annotations (readOnlyHint, openWorldHint, idempotentHint), the description reveals substantial behavioral context: it returns a structured success object with evidence as a verbatim quote, and explicitly enumerates refusal reasons when the data doesn't directly answer. It also discloses the extra LLM call cost. 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 front-loaded with its core purpose and then efficiently details the return contract and usage guidance. Every sentence contributes essential information for selection and correct invocation, with no filler or repetition. The refusal-reason enumeration, though detailed, is necessary because no output schema exists.

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 fully covers the return format, success and failure modes, refusal reasons, and when to choose it over a sibling. The cost trade-off and high-stakes use case are clearly stated. No information an agent needs to call this tool correctly is missing.

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%, so all parameters are already documented in the schema. The description adds no additional parameter-level meaning beyond indicating that the input is a natural-language 'question' — which the schema already states. This meets the baseline for high schema coverage.

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 specific verb ('extracts the answer'), a clear resource ('answer mode for high-stakes reads'), and a defining behavioral trait ('hallucination-resistant', 'using ONLY what the tool result contains'). It explicitly contrasts with ask_pipeworx, making the distinction 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?

It explicitly states when to use this tool (answers that will be quoted, cited, or acted on, especially in financial/legal/medical contexts) and when not to ('prefer ask_pipeworx for casual lookups'). It also names the alternative (ask_pipeworx) and discloses the extra cost, giving the agent a clear decision rule.

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