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

Discloses the refusal behavior and exact response shape (both success and error refusals like not_in_source, no_tool_match), which goes well beyond the basic readOnly/idempotent annotations. It also reveals an extra LLM call cost and the grounding constraint 'using ONLY what the tool result contains', informing the agent of operational consequences.

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?

Every sentence carries a distinct piece of information: purpose, mechanics, return contract, usage policy, and cost/alternative. While dense, it remains structured and front-loaded with the most important qualifier first, with 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?

No output schema exists, but the description supplies a full contract for both success and refusal paths, covering return fields, reasons, and the single required input. Together with annotations and schema, an agent has everything it needs to invoke correctly.

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?

All 6 params are aliases for question and the schema already documents each as an 'Alias for question' (100% coverage). Description adds no parameter semantics beyond what input schema provides, so the baseline 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 opens with a specific value proposition ('Hallucination-resistant answer mode for high-stakes reads') and clearly differentiates from the sibling 'ask_pipeworx' by describing the same routing but a grounded extraction step. It states a concrete action (extract answer using ONLY the tool result) and resource (Pipeworx), so an agent can distinguish it from siblings.

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?

Explicitly tells the agent when to choose this tool: 'Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts,' with concrete domains. It also states when not to use it: 'prefer ask_pipeworx for casual lookups,' naming the alternative and the cost tradeoff.

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