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

Annotations already signal read-only, open-world, idempotent behavior. The description goes well beyond that by disclosing latency cost, the exact success return shape with verbatim evidence, and the explicit refusal_reason enum when data doesn't directly answer. No stated behavior contradicts the 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 every sentence earns its place: purpose, mechanism, return/refusal contract, usage trigger, and cost tradeoff. It is front-loaded with the most important information and well organized despite its length.

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 tool with no output schema, the description fully specifies return structure on both success and refusal paths, names all refusal reasons, explains the cost implication, and gives concrete use cases. An agent has enough to select and invoke it correctly without additional information.

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 question parameter and its aliases. The description adds no parameter-specific semantics beyond the schema, so the baseline score of 3 applies.

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 states a specific mode—'Hallucination-resistant answer mode for high-stakes reads'—and contrasts it with ask_pipeworx, naming the exact mechanism: same routing, then extraction using only the tool result. This clearly differentiates it from its siblings and removes ambiguity about what it does.

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?

The description explicitly says when to use it ('whenever an answer will be quoted, cited, or acted on... must not invent facts'), gives concrete domains, and names the alternative ('prefer ask_pipeworx for casual lookups') plus the cost tradeoff. This is explicit when/when-not guidance.

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