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

Annotations already indicate this is read-only, non-destructive, idempotent, and open-world. The description goes beyond that by disclosing the strict extraction-only behavior, the explicit refusal mechanism, all possible refusal reasons, and the additional cost relative to ask_pipeworx. This gives the agent a clear mental model of success and failure behavior.

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 but every sentence earns its place: core behavior, return shape, refusal behavior, use cases, and cost tradeoff are all covered in four sentences. The key grounded/high-stakes distinction is front-loaded, and no filler is present.

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 one logical parameter and no output schema, the description is remarkably complete: it explains the output contract on success, all refusal modes, when to choose this over the sibling, and the behavioral guarantee that prevents hallucination. An agent has everything needed to select and invoke it correctly.

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 input schema already covers 100% of the parameters and fully describes the question field and its aliases. The description adds no parameter-level detail such as length limits, formatting, or example inputs, 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 clearly identifies this as a hallucination-resistant answer mode that routes like ask_pipeworx, fetches data, and extracts answers only from tool results. It states the specific resource and behavior and explicitly distinguishes itself from ask_pipeworx, making sibling confusion unlikely.

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 says exactly when to use this tool: whenever the answer will be quoted, cited, or acted on and the agent must not invent facts, with concrete domains like financial verdicts, legal claims, and medical lookups. It also gives the alternative and the when-not-to-use condition: prefer ask_pipeworx for casual lookups because this mode costs an extra LLM call.

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