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

The description discloses behavior well beyond the annotations: it guarantees grounding only in the tool result, returns structured success/refusal objects with specific refusal reasons, and is explicit about the extra LLM call cost. The annotations already mark it read-only, idempotent, and non-destructive; nothing here contradicts them.

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 contributes: purpose, mechanism, return shape, refusal behavior, use cases, and tradeoff. It front-loads the most important phrase ('Hallucination-resistant answer mode') and avoids 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, the description provides the exact success and refusal JSON shapes, lists possible refusal reasons, explains the extra cost, and gives clear usage boundaries. An agent has all the information needed to invoke the tool correctly and interpret its result.

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 has 100% coverage because every parameter is documented as an alias for 'question' and the schema explains the aliases. The description does not add new parameter semantics, so a 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 opens with a specific purpose ('Hallucination-resistant answer mode for high-stakes reads') and then explains the mechanism: it routes like ask_pipeworx, selects from 5,767 tools, fetches data, and extracts answers only from the tool result. This clearly identifies the tool's function and distinguishes it from the sibling ask_pipeworx.

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?

The description explicitly states when to use the tool ('whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts') and when not to ('prefer ask_pipeworx for casual lookups'). It even names the specific alternative and the cost tradeoff, leaving no ambiguity.

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