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

The description discloses substantial behavior beyond annotations: it returns evidence with verbatim quotes, may explicitly refuse with a specific refusal_reason enum, extracts only from tool result content, and costs one extra LLM call. Annotations already indicate read-only, idempotent, open-world behavior, and the description does not contradict them.

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 well front-loaded, opening with the defining trait ('Hallucination-resistant answer mode') before detailing return shape, use cases, and cost tradeoff. Some minor redundancy exists in the refusal explanation, but overall each sentence contributes useful decision-making information.

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 specifying the exact success response fields and the refusal contract, including enum values. It also covers cost, preferred sibling, and appropriate use cases, leaving no critical gap for an agent deciding whether and how to call this 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 every parameter is documented as an alias for 'question', so the schema already carries the full parameter meaning. The tool description adds no further parameter semantics beyond indicating the routing pipeline, which is not needed at this baseline.

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, differentiated purpose: a hallucination-resistant answer mode that extracts answers only from tool results and issues refusals when data is insufficient. It clearly distinguishes from ask_pipeworx by emphasizing grounded answers, evidence, and refusal behavior, and names the sibling it parallels ('Same routing as ask_pipeworx').

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?

Use is explicitly scoped to high-stakes contexts where answers will be quoted, cited, or acted on, and where inventing facts is unacceptable. It also names the alternative, ask_pipeworx, and gives a clear cost-based preference rule: prefer ask_pipeworx for casual lookups.

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