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

Annotations already signal read-only, open-world, idempotent, non-destructive behavior, and the description adds substantial behavioral context beyond this: extraction limited to the tool result, structured refusal reasons (not_in_source, no_tool_match, etc.), evidence verbatim quotes, and the extra LLM call cost. No contradiction with annotations.

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 is information-dense and earns its place: the first sentence summarizes the mode, the second details routing and extraction, the third specifies the return/refusal contract, and the final sentence gives usage guidance and cost trade-off. No fluff or redundancy.

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 fully specifies both success and refusal response shapes, enumerates possible refusal_reason values, explains the mechanism, names when to use it, and gives the cost comparison with ask_pipeworx. Nothing essential for correct invocation is missing.

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%, with all six parameters documented as aliases for 'question'. The description adds no parameter-specific detail, but it does not need to because the schema fully defines the sole meaningful input. 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 states a distinct purpose: a hallucination-resistant answer mode grounded strictly in tool results, with an explicit success/refusal return contract. It differentiates from siblings by naming ask_pipeworx as the same routing but ungrounded mode, and the 'Grounded' title reinforces the uniqueness.

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: when answers will be quoted, cited, or acted on, and hallucination is unacceptable. It also gives a clear 'when not' by recommending ask_pipeworx for casual lookups due to the extra LLM call cost, naming the exact alternative.

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