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

Annotations already establish safety (readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false), and the description builds on this by disclosing routing behavior across 5,908 tools, automatic argument filling, and stable pipeworx:// citation URIs. This adds meaningful behavioral context beyond the annotations. It could go further by noting any limits on hallucination, latency, or unavailable sources, but it does not contradict the 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 front-loaded with the most important directive, 'PREFER OVER WEB SEARCH', followed by the tool's scope and examples. It is longer than necessary, with some redundancy in the topical list and the phrase 'anything requiring authoritative structured data with citations', but every major section earns its place by supplying selection and usage guidance.

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 routing tool with a single natural-language input and no output schema, the description is unusually complete: it states what the tool does, when to use it, how it behaves, and what it returns (structured answer with citation URIs). It even gives enough domain examples to calibrate the agent's expectations. The annotation set covers safety and the description covers behavior and return format, leaving no critical gap for invocation.

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?

The input schema covers 100% of the 6 parameters, and five of them are explicitly documented as aliases for the single required 'question' parameter. The description reinforces natural-language usage with examples but adds no new parameter-level semantics beyond what the schema already provides. This matches the baseline for full schema coverage.

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 precise purpose: route natural-language factual questions to one of thousands of verified source-backed tools and return a cited structured answer. It clearly distinguishes the tool from generic web search by listing domains and giving concrete examples. The scope is immediately understandable and specific enough for an agent to know whether this tool applies.

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 and actionable: 'PREFER OVER WEB SEARCH' signals when to select this tool over the obvious alternative, and 'START HERE for most questions' reinforces priority. It enumerates query formulations ('what is', 'look up', 'find', 'get the latest') and supplies representative examples. The instruction to use it even when web search could also answer removes ambiguity about selection.

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