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

Annotations already establish read-only, open-world, idempotent, and non-destructive behavior. The description adds substantial behavioral context beyond the annotations: it explains the grounding mechanism, documented success and refusal result shapes, specific refusal reasons, and the extra cost relative to ask_pipeworx. No contradiction with annotations.

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 without padding. It front-loads the core purpose, then covers behavior, output shape, usage guidance, and cost trade-offs in a compact set of sentences. Every clause adds value.

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?

For a single-parameter tool with no output schema, the description is remarkably complete: it documents the return shape, refusal reasons, behavioral guarantees, cost implications, and when to choose the sibling instead. An agent has everything needed to select and invoke the 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 description coverage is 100%, with the single required parameter 'question' fully described including its aliases. The description itself adds little parameter-level detail, but the schema already carries the full burden, 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 states a specific, differentiated purpose: a hallucination-resistant answer mode that extracts answers only from tool results. It explicitly contrasts with ask_pipeworx, and the grounding behavior is described with concrete detail, so an agent can distinguish this tool from its 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?

The description explicitly says when to use this tool — whenever an answer will be quoted, cited, or acted on, and facts must not be invented — and when not to use it: prefer ask_pipeworx for casual lookups because this mode costs an extra LLM call. This is clear, actionable routing guidance.

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