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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, and the description does not contradict them. It goes further by disclosing refusal behavior with specific refusal_reason values, promising verbatim evidence quotes, noting the extra LLM call cost, and explicitly stating the tool will not invent facts. This is rich behavioral context beyond the 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?

Although longer than a one-liner, every sentence earns its place: purpose, mechanism, return shape, refusal reasons, use cases, and cost tradeoff are all compressed into a dense but readable block. The critical grounding behavior and refusal semantics are front-loaded, and the alternative routing is stated at the end without wasted words.

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?

Despite having no output schema, the description fully specifies the success return shape and the explicit refusal shape with enumerated refusal_reason values. It covers when to use, when not to use, cost implications, and the relationship to ask_pipeworx. For a tool of this complexity, nothing an agent needs to decide or invoke 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%, with all six parameters documented as aliases for the natural-language question. The description adds no parameter-level details beyond the schema, so the baseline of 3 applies. It mentions natural-language use context but does not need to compensate for any schema gap.

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 identifies a specific verb ('EXTRACTS the answer using ONLY what the tool result contains') and a clear resource ('Pipeworx' with grounded/hallucination-resistant behavior). It explicitly distinguishes itself from the sibling ask_pipeworx by naming the same routing but adding extraction constraints. The success and refusal return structures further clarify the tool's purpose.

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 provides a concrete alternative: 'prefer ask_pipeworx for casual lookups.' It also names the sibling it routes identically to, so an agent can choose between grounded and non-grounded variants without ambiguity.

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