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

Annotations declare readOnly, openWorld, idempotent, and non-destructive behavior, and the description adds substantial context beyond them: it states the tool may return an explicit refusal with specific refusal_reason values, includes verbatim evidence, and discloses the cost tradeoff of one extra LLM call. It also transparently describes source selection and data-fetching behavior. No contradiction with annotations exists.

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?

Every sentence earns its place: purpose, mechanics, return contract, refusal modes, usage guidance, and cost tradeoff are all packed in without redundancy. The most important differentiator ('hallucination-resistant') is front-loaded, and the refusal-reason enum is precise rather than hand-wavy.

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?

There is no output schema, so the description compensates by fully specifying the success response fields and the refusal response variants. It also covers when to use the tool, when not to, how it differs from the sibling, and its cost profile. An agent has everything needed to decide and invoke 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 schema covers 100% of parameters and already documents the single required question parameter, including aliases (query, q, prompt, text, input). The description reinforces that the tool answers a natural-language question but does not need to add parameter-level detail because the schema carries that burden.

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, differentiating purpose: 'Hallucination-resistant answer mode for high-stakes reads.' It then clearly states the mechanism — same routing as ask_pipeworx, but extracts answers using ONLY tool results — and defines success and refusal return shapes. This distinguishes it from sibling ask_pipeworx and ask_pipeworx_beta without needing to inspect the schema.

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?

Explicit when-to-use guidance is provided: 'Use whenever an 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 an exclusion and alternative: 'prefer ask_pipeworx for casual lookups.' This fully routes an agent between the two siblings.

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