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

The annotations already mark the tool as read-only, idempotent, and open-world, but the description adds significant behavioral detail: it may return a structured refusal instead of inventing an answer, lists the refusal reasons, and emphasizes that extraction is limited to tool-result content. This goes far beyond the annotations 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 well-organized: purpose first, then return contract, then usage context, then cost trade-off. Every sentence contributes selection or behavioral information, and the refusal-reason list earns its place by setting accurate expectations.

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 specifies the success shape, the refusal shape, refusal reason enums, when to use the tool, and when to choose the sibling instead. With only one required natural-language parameter, an agent has everything needed to invoke and interpret the tool 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%, with all six parameters documented as aliases for a natural-language question. The description does not add parameter-level detail, but the baseline of 3 applies because the schema already carries the full burden of parameter 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 clearly identifies this as a hallucination-resistant, grounded answer mode and contrasts it with ask_pipeworx: same routing, but the answer is extracted only from the tool result. It states the specific behavior (fetch, extract, refuse when unsupported) and includes the return shape, making the purpose unmistakable.

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 gives explicit when-to-use guidance ('Use whenever an answer will be quoted, cited, or acted on...') and explicit when-not-to-use guidance ('prefer ask_pipeworx for casual lookups'). It also names the alternative tool (ask_pipeworx) and explains the cost trade-off, so an agent can route decisively.

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