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

Annotations already mark readOnlyHint=true and idempotentHint=true, but the description adds substantial behavioral detail beyond that: it returns a structured {answer, evidence, confidence, source, fetched_at, refusal_reason} object, enumerates the exact refusal reasons, and states that extraction uses only what the tool result contains. No contradiction with 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?

The description is dense but purposeful; every sentence covers a distinct aspect: mode, mechanism, return shape, refusal shape, use case, and cost tradeoff. It is slightly long, but the information density is high and front-loaded with the most important distinction.

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 one simple parameter, no output schema, and rich annotations, the description fully equips an agent: it explains the return contract, refusal contract, when to use it, when not to use it, and how it differs from the sibling. Nothing critical 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% and the schema already documents the single question parameter plus its aliases. The tool description does not need to repeat parameter details, so the baseline of 3 applies; it adds no extra parameter semantics beyond what the schema provides.

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 opens with a specific mode, 'Hallucination-resistant answer mode for high-stakes reads', and explains its mechanism: it extracts answers only from tool results. It also explicitly contrasts with the sibling ask_pipeworx, saying it has the same routing but a grounded extraction step, so an agent can clearly distinguish it.

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: whenever an answer will be quoted, cited, or acted on, and facts must not be invented. It also provides the tradeoff and exclusion: it costs one extra LLM call and 'prefer ask_pipeworx for casual lookups', naming the alternative directly.

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