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

The description discloses key behavioral traits beyond annotations: it only extracts answers from tool results, returns verbatim evidence, and provides specific refusal reasons. It also mentions the extra LLM call cost, which is not captured by 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?

Three sentences pack purpose, behavior, output shape, refusal reasons, and usage guidance without unnecessary fluff. The structure flows logically from mode to output to when-to-use.

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?

Even though no output schema is provided, the description thoroughly details the success and refusal return shapes, including allowed refusal_reason values. It also gives domain examples and explicitly contrasts with ask_pipeworx, making the tool self-contained.

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?

The schema already fully covers all six parameters, including aliases and the required question parameter. The tool description does not add parameter-specific guidance beyond what the schema provides, so the neutral baseline 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?

Clearly identifies the tool as a hallucination-resistant answer mode for high-stakes reads, naming the specific verb 'extract' and the resource. It also distinguishes itself from ask_pipeworx by emphasizing grounded answers and refusal 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 the tool: for high-stakes reads, or whenever an answer will be quoted, cited, or acted on, and when the agent must not invent facts. It also explicitly says to prefer ask_pipeworx for casual lookups, providing a clear alternative.

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