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

Annotations already mark readOnly/openWorld/idempotent, and the description goes further by explaining the grounded extraction behavior, the exact refusal reasons, and the extra-LLM-call cost. This provides meaningful behavioral context beyond the annotations, with no 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 dense and front-loaded with the most important distinction ('Hallucination-resistant answer mode for high-stakes reads'). Some detail, like exact source counts, could be trimmed, but every sentence contributes to selection or invocation decisions.

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 compensates fully by documenting the success return shape and the refusal structure with enumerated reasons. Combined with annotations, the agent has everything needed to invoke the tool correctly and interpret its result.

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 documents the 'question' parameter plus aliases clearly. The tool description adds no parameter-specific semantics, but it doesn't need to since the schema fully covers the single conceptual parameter.

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 names a specific behavior — halluncination-resistant grounded answering — and differentiates it from sibling ask_pipeworx by stating it extracts answers 'using ONLY what the tool result contains' and returns explicit refusals. This makes the tool's role and boundary unmistakable.

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?

It explicitly states when to use this tool ('whenever an answer will be quoted, cited, or acted on... must not invent facts') and when not to ('prefer ask_pipeworx for casual lookups'). It even quantifies the cost tradeoff, giving the agent a clear decision rule.

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