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

Discloses the exact refusal contract with refusal_reason enum, success return shape, evidence quoting behavior, and the extra LLM call cost. Annotations already declare read-only/non-destructive/idempotent, so the description adds substantial behavioral detail without contradicting them.

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 mostly earns its length: the core distinction is front-loaded, the return contract is compactly specified, and the cost/usage trade-off is explicit. It could be tightened structurally, but there is little waste.

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 read-only query tool, the description covers purpose, trust boundary, success and failure return shapes, example use cases, and cost relative to the sibling tool. Nothing material is missing for an agent to decide when to call it and what to expect.

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 already documents the single required question parameter and its aliases, so schema coverage is high and the baseline is 3. The description does not add parameter-level meaning beyond mentioning that the tool 'fills arguments' internally, which is about routing rather than the question parameter itself.

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?

Describes a concrete, distinct mode: 'hallucination-resistant answer mode' that extracts answers 'using ONLY what the tool result contains.' It differentiates from the likely sibling ask_pipeworx by naming the shared routing while adding the grounded-evidence behavior.

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?

Explicitly states when to use ('whenever an answer will be quoted, cited, or acted on... must not invent facts'), gives example domains, and directly contrasts with ask_pipeworx: 'prefer ask_pipeworx for casual lookups'.

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