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

Annotations already mark it read-only and non-destructive, so the safety profile is covered by structured data. The description adds valuable context beyond that: refusal reason taxonomy, evidence as verbatim quote, extra LLM call cost, and the guarantee that extraction uses only tool results. This goes well beyond what annotations provide.

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 long but dense, with every clause contributing a distinct behavioral or usage fact. It is front-loaded with the core purpose, then flows into return behavior, refusal semantics, and usage guidance. Only minor trimming could be done without losing 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?

With no output schema present, the description fully specifies the success return shape, the refusal return shape, and the list of possible refusal reasons. It also covers cost tradeoffs and applicable scenarios, so an agent has everything needed to decide to call it and interpret its result.

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 description adds no parameter-level meaning beyond the schema's already complete alias documentation. The baseline of 3 is appropriate because the schema carries the full parameter burden and the description does not need to compensate.

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, action-oriented purpose: a hallucination-resistant answer mode that routes through Pipeworx and extracts answers only from tool results. It clearly differentiates itself from ask_pipeworx by emphasizing evidence, confidence, and explicit refusals, so an agent can tell them apart immediately.

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 this mode when an answer will be quoted, cited, or acted on, and when the agent must not invent facts. It also names the alternative, ask_pipeworx, and explicitly says to prefer it for casual lookups, leaving no ambiguity about when to choose each.

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