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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, and the description adds substantial behavioral context beyond them: it promises extraction 'using ONLY what the tool result contains', defines the explicit refusal structure with reason enums, and notes the extra LLM cost. It even specifies the exact success return shape despite there being no output schema.

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 information-dense but every sentence earns its place: mode, routing behavior, output contract, refusal cases, usage trigger, and cost tradeoff. It is front-loaded with the most decision-relevant trait ('Hallucination-resistant answer mode') and contains no 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?

Given the tool's complexity, the description is complete: it covers success output fields, failure refusal reasons, when to use and when not to, cost implications, and its relationship to ask_pipeworx. The 100% schema coverage handles parameter detail, and annotations handle safety invariants, so nothing an agent needs to call this correctly is 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 coverage is 100% and all six parameters are documented aliases for the single required 'question' field, so the description does not need to explain parameters. The description does not add parameter-level meaning beyond the schema, but the baseline of 3 is appropriate because the schema fully carries the 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 states a specific verb and resource: it is a hallucination-resistant answer mode that routes to the appropriate tool, fetches data, and extracts an answer using only the tool result. It explicitly differentiates itself from sibling ask_pipeworx by its grounded extraction and refusal behavior, so an agent can distinguish it without opening schemas.

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' in high-stakes contexts. It also names the alternative ask_pipeworx and states the tradeoff ('Costs one extra LLM call ... prefer ask_pipeworx for casual lookups').

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