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

Describes the read-only, grounded nature, lists explicit refusal reasons, and states the extra LLM call cost. Annotations already indicate readOnly and non-destructive, and the description adds meaningful behavioral detail without contradiction.

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 clear and well-structured but repeats 'ask_pipeworx' and 'answer' several times. Still, every sentence contributes useful 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?

Despite no output schema, the description fully compensates by specifying the return shape, refusal reasons, and the key behavioral difference from ask_pipeworx, making the tool's use and outcomes clear.

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 covers all six parameters, and the description adds that the question is in natural language and explicitly lists all accepted aliases. This goes slightly beyond the schema's alias descriptions.

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?

Clearly identifies this as a hallucination-resistant, evidence-only answer mode for high-stakes reads, and differentiates it from ask_pipeworx by the grounded extraction behavior.

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 states when to use it — when answers will be quoted, cited, or acted on — and when to 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.