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

The description reveals important behavioral traits beyond the annotations: it costs one extra LLM call, extracts only from tool results, returns structured success/refusal shapes, and enumerates specific refusal_reason values. The annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, and the description does not contradict 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 appropriately structured: purpose first, then return/refusal details, then usage guidance and cost tradeoff. Every sentence carries useful information, though the output-shape enumeration makes it longer than minimal.

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 rightly explains the success and refusal return structures, including refusal reasons. It also covers the extra-cost tradeoff, the alternative tool, and the high-stakes use cases. Nothing essential for correct invocation appears to be missing.

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 the schema already documents the single natural-language question parameter, including aliases. The description adds no parameter-specific semantics beyond the schema, 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 opens with a specific, behavior-rich purpose: 'Hallucination-resistant answer mode for high-stakes reads.' It then clearly distinguishes itself from the sibling ask_pipeworx by explaining that it extracts answers using ONLY the tool result and returns a refusal when the data doesn't answer. This makes the tool's role and its differentiation from siblings explicit.

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 gives explicit when-to-use guidance: 'Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts.' It also states the alternative and the condition for choosing it: 'prefer ask_pipeworx for casual lookups.' This is strong, actionable routing information.

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