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

The description discloses important behavior beyond the annotations: it extracts only from the tool result, returns a refusal instead of guessing, and enumerates concrete refusal reasons such as 'not_in_source' and 'data_truncated.' It also details the success and refusal response shapes, which is valuable since there is no output schema. The readOnlyHint and idempotentHint annotations are consistent with this non-mutating, grounded behavior.

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 long but dense and front-loaded with the core purpose. Each clause adds a meaningful fact: extraction constraint, return shapes, refusal reasons, use cases, and cost/alternative. It is slightly longer than strictly necessary, but given the complexity and the absence of an output schema, the length is largely justified.

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?

The description is complete for a high-stakes question-answering tool. It explains the routing behavior, the grounded extraction guarantee, the exact success and refusal return formats, the failure categories, and the decision between this tool and ask_pipeworx. Nothing essential is missing for an agent to select and invoke it 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%: all six parameters are aliases for 'question' and are well-documented in the schema. The description does not add new parameter semantics, but the schema already fully covers what the agent needs to know, so the baseline of 3 applies.

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 identifies a distinct answer mode: it routes like ask_pipeworx but then 'EXTRACTS the answer using ONLY what the tool result contains.' The verb 'extracts' plus the resource 'answer' makes the purpose concrete. It also contrasts with ask_pipeworx, making the tool's unique function immediately clear.

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.' It also names the alternative and the trade-off: 'prefer ask_pipeworx for casual lookups' and notes the extra LLM call cost. This fully routes the agent between the two siblings.

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