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

The description fully discloses the success return shape, all possible refusal reasons, the extraction-only behavior, and the added LLM cost. Annotations already indicate read-only/idempotent behavior, but the description adds substantially more behavioral context without contradicting 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 front-loaded with the core purpose, then moves through return shape, refusal handling, usage guidance, and cost trade-off. Every sentence adds distinct information; the length is justified by the need to specify refusal semantics and usage boundaries.

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?

Despite having no output schema, the description explains exactly what the tool returns and all failure/refusal modes. Combined with full schema coverage for the single parameter and safety-related annotations, an agent has everything needed to select and invoke this tool 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?

Schema coverage is 100%, and the schema already documents the single required 'question' parameter plus all aliases. The description adds no parameter-specific detail, but none is needed because the schema fully handles semantics.

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 — 'Hallucination-resistant answer mode for high-stakes reads' — and contrasts itself with ask_pipeworx by stating it uses 'ONLY what the tool result contains.' This makes the tool's identity and boundary clear even among many siblings.

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 states when to use it ('whenever an answer will be quoted, cited, or acted on'), gives concrete high-stakes examples, and tells the agent to prefer ask_pipeworx for casual lookups due to the extra LLM call cost. This is strong when/when-not guidance.

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