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

Beyond the readOnly/idempotent annotations, it discloses exact success and refusal return shapes, enumerates all refusal_reason values, and states the 'uses ONLY what the tool result contains' grounding constraint. It also surfaces the extra-call cost tradeoff. There is no contradiction with the 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?

The summary identity is front-loaded, followed by routing mechanics, the output contract, usage guidance, and a cost tradeoff. Every sentence adds decision-relevant information with no filler, and the return object is described compactly.

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?

For a tool with no output schema, the description adequately documents the success payload, failure modes, refusal reasons, and grounding behavior. Since only one parameter is required, no invocation detail is missing, and the description also covers when not to use it.

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 all six parameters are aliases of the single 'question' field already documented as natural language input. The description reinforces the high-stakes grounded use case but adds no parameter-level meaning beyond what the schema already provides.

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?

It opens by defining the tool as a 'hallucination-resistant answer mode for high-stakes reads' and specifies the exact extraction contract: answer, verbatim evidence, confidence, and explicit refusal when the data doesn't answer. This clearly distinguishes it from the sibling ask_pipeworx and other tools while naming its routing relationship.

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 says to use it 'whenever an answer will be quoted, cited, or acted on,' names concrete grounded-answer domains, and gives the exclusion: prefer ask_pipeworx for casual lookups due to the extra LLM call. The alternative tool is named precisely, with a clear selection condition.

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