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

Beyond the already non-destructive readOnly/idempotent annotations, the description discloses the exact refusal contract with refusal_reason enum values, the evidence/verbatim quote behavior, the returned fields, and the 'ONLY what the tool result contains' constraint. This is unusually transparent about failure modes and guarantees.

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 clause earns its place: purpose, routing behavior, success and refusal return shapes, usage criteria, and cost/alternative guidance. It is front-loaded with the most important characterization — hallucination-resistant, high-stakes mode — before diving into mechanics.

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 enumerates the full success return shape and all refusal reasons, making the tool callable without guessing at responses. This is complete for a one-required-parameter, high-stakes lookup tool.

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 all six parameters are documented as aliases for a natural-language question. The description adds no additional parameter-specific semantic detail, but the schema already carries that burden adequately, so the 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 identifies this as a grounded, hallucination-resistant answer mode and explicitly contrasts it with ask_pipeworx, its primary sibling. It states what the tool does — route, fetch, and extract an answer only from tool results — so an agent can distinguish it from other research and ask tools without needing additional context.

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 gives explicit when-to-use guidance: 'Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts.' It also names the alternative for casual lookups — 'prefer ask_pipeworx for casual lookups' — and discloses the extra LLM call cost that should factor into the choice.

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