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

The description discloses substantial behavior beyond annotations: it uses only tool-result content, returns a structured response with evidence and refusal reasons, and explicitly lists refusal reasons such as 'not_in_source' and 'data_truncated'. This aligns with readOnlyHint/idempotentHint and adds meaningful operational context that annotations alone do not provide.

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 front-loaded with the core purpose and every sentence earns its place: behavior, output/refusal format, usage context, and cost tradeoff. It packs a lot of necessary detail into a compact, well-structured form without 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?

With no output schema present, the description compensates thoroughly by specifying the success return shape and the refusal return shape, including all refusal reasons. It also covers routing behavior, cost, and usage boundaries, making the tool fully operable for an agent in a high-stakes context.

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%, so the input schema already fully documents the 'question' parameter and its aliases. The tool description adds no parameter-specific semantics beyond the idea that arguments are filled, so the baseline of 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 identifies a specific verb and resource with a clearly stated purpose: a hallucination-resistant answer mode for high-stakes reads that extracts answers only from fetched tool results. It explicitly distinguishes itself from ask_pipeworx by emphasizing grounded extraction and refusal behavior rather than general answering.

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 gives explicit when-to-use guidance: 'Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts,' with concrete examples. It also names the alternative and the condition to prefer it: 'prefer ask_pipeworx for casual lookups' and notes the extra LLM call cost.

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