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

Annotations already mark the tool read-only, idempotent, non-destructive, and open-world, and the description does not contradict those. It adds valuable behavior beyond annotations: the tool returns verbatim evidence, confidence, source, fetched_at, and an explicit refusal with enumerated refusal_reason values when the data does not directly answer.

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 front-loads the key differentiator ('Hallucination-resistant answer mode for high-stakes reads') and then packs routing, return contract, refusal reasons, use cases, and cost comparison into a dense but efficient block. Every sentence contributes information the agent needs; there is no filler.

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?

Because there is no output schema, the description fully specifies the success shape and the refusal shape with possible refusal_reason values. It clarifies cost, relationship to ask_pipeworx, and the high-stakes conditions under which the tool should be chosen, leaving no significant gap for an agent deciding whether and how to call it.

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 coverage is 100% and the schema already documents the single question parameter and its aliases (q, query, prompt, text, input), so the baseline applies. The description adds no parameter-level detail beyond saying the internal routing 'fills arguments,' which is about behavior rather than input 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 names a specific verb-plus-resource behavior: a grounded, hallucination-resistant answer mode that routes like ask_pipeworx but extracts answers only from tool results. It explicitly distinguishes itself from the sibling ask_pipeworx by the extraction guarantee and the structured refusal 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?

It gives an explicit when-to-use rule: whenever an answer will be quoted, cited, or acted on in high-stakes contexts (financial, legal, medical, public statements). It also states the alternative: prefer ask_pipeworx for casual lookups because grounded mode costs an extra LLM call.

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