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

The description discloses key behaviors beyond annotations: routing logic, argument filling, fetching, grounded extraction, return shape, refusal reasons, and the extra LLM call cost. Annotations already indicate read-only/idempotent, and the description adds rich 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 and contains dense, useful detail such as the refusal taxonomy and cost trade-off. It is somewhat long, but every section earns its place given there is no output schema to carry the return-shape information.

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 lack of an output schema, and the need to distinguish it from sibling tools, the description is remarkably complete. It covers return values, refusal cases, cost, routing behavior, and when to use it, so an agent has enough information to invoke it 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%, so the schema already fully documents the single question parameter and its aliases. The description adds no new parameter-specific meaning beyond implying a natural-language question, which matches the schema's stated baseline.

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: a hallucination-resistant answer mode for high-stakes reads. It explicitly contrasts with ask_pipeworx by saying it extracts answers using ONLY what the tool result contains, so an agent can distinguish it from siblings 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?

Usage guidance is explicit: use when an answer will be quoted, cited, or acted on and facts must not be invented, with concrete examples. It also tells the agent to prefer ask_pipeworx for casual lookups, naming the alternative and the condition for choosing it.

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