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

Annotations already mark the tool read-only, idempotent, and non-destructive, so the description builds on that with valuable behavioral detail: it EXTRACTS the answer only from tool results, returns evidence as a verbatim quote, and explicitly refuses rather than fabricating when data is insufficient. The refusal_reason enum adds precise transparency about failure modes.

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 every sentence earns its place: purpose, mechanism, return/refusal contract, usage guidance, and cost trade-off. It is front-loaded with the most important differentiator ('Hallucination-resistant') and uses structured details like the refusal_reason enum and return fields compactly.

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 there is no output schema, the description fully specifies the success return object and the refusal object, including possible refusal reasons. It also states the extra-call cost, makes the use case concrete, and covers the routing behavior inherited from ask_pipeworx. Nothing essential for correct invocation or expectation-setting 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 coverage is 100%: the only meaningful parameter is 'question', and the schema documents six aliases for it. The description adds no parameter-specific detail beyond saying arguments are filled during routing, which is useful context but not needed because the schema already fully defines the input semantics.

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 a specific verb and resource ('answer mode'), defines its core behavior as hallucination-resistant grounded extraction, and explicitly distinguishes it from the sibling ask_pipeworx by stating the same routing but stricter answer provenance. This makes it immediately identifiable among the large sibling list.

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?

Provides explicit when-to-use guidance: high-stakes reads where answers may be quoted, cited, or acted on, such as financial, legal, medical, or public-statement lookups. It also names the alternative and gives the trade-off ('Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups'), so the agent can route correctly without ambiguity.

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