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

Annotations already signal read-only, idempotent, non-destructive behavior, and the description adds substantial behavioral context beyond them: it extracts using ONLY the tool result, returns verbatim evidence, refuses explicitly with specific refusal_reason values, and incurs an extra LLM call. This fully discloses failure modes and resource implications.

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 information-dense but every sentence earns its place: primary purpose first, then mechanism, return contract, refusal behavior, use cases, and cost/alternative trade-off. The front-loaded core sentence lets an agent immediately grasp the tool's role.

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?

With no output schema, the description fully compensates by spelling out the success response shape, the refusal response shape, and all refusal reasons. It also covers the decision boundary with its sibling and the cost implication, making the definition complete for invocation and selection.

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%, so the schema already documents the question parameter and its alias set. The description adds no new parameter-specific meaning, but that is acceptable because the schema carries the load; baseline 3 is appropriate.

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 states it is a hallucination-resistant answer mode that extracts answers exclusively from tool results and returns evidence with refusals. It explicitly distinguishes itself from sibling ask_pipeworx via the 'casual lookups' contrast, so an agent can tell them apart without opening either schema.

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 lists high-stakes domains. It also names the alternative ask_pipeworx and advises preferring it for casual lookups due to the extra LLM call cost, leaving no ambiguity.

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