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

Annotations already establish read-only, open-world, idempotent, non-destructive behavior. The description adds valuable context beyond those hints: it discloses that answers are extracted only from fetched data, that refusals are explicit with specific reasons, and that it costs one extra LLM call. This paints a full behavioral picture.

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 detailed but each sentence earns its place: it explains the mechanism, the return/refusal contract, ideal use cases, and the trade-off versus the sibling. It is front-loaded with the core behavior, though the enumeration of refusal reasons makes it slightly dense.

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?

With no output schema, the description carried the burden of explaining the return format and failure modes, and it does so thoroughly. It also communicates routing behavior, source scope, and cost trade-offs, leaving little ambiguity for an agent deciding whether and how to call it.

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%, and the schema itself already documents the 'question' parameter and its aliases. The description does not add new parameter-level meaning beyond what the schema provides, 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 behavior: a hallucination-resistant answer mode that routes like ask_pipeworx, fetches data, and answers only from tool results. It clearly differentiates itself from the sibling ask_pipeworx by emphasizing grounded extraction and refusal handling.

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 this tool ('whenever an answer will be quoted, cited, or acted on... must not invent facts') and when not to ('prefer ask_pipeworx for casual lookups'), naming the alternative directly. This gives an agent unambiguous selection criteria.

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