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

With readOnlyHint, openWorldHint, and idempotentHint already present, the description adds meaningful behavior beyond annotations: it explains that the tool routes to one of 5,724 tools, fills arguments, and returns stable pipeworx:// citation URIs. It also notes it is a single fast call that works on every tier. This gives useful operational context, though it does not discuss failure modes or result formatting in depth.

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 well-structured and front-loaded with the most important directive: 'PREFER OVER WEB SEARCH'. It earns its length by covering trigger phrases, examples, alternatives, and routing behavior in a logical order. Slight redundancy exists around the alias list, but overall it is appropriately sized for a default entry-point tool.

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 and the absence of an output schema, the description covers the essential context: when to use it, what types of questions it handles, how it behaves (routing and citations), and when to choose alternatives. It does not document exact result structure, but it names the output as a structured answer with citation URIs, which is sufficient for an agent 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% and all six parameters are documented as aliases for the same natural-language question field. The description reinforces this with examples but does not add new parameter-level semantics beyond what the schema already provides, so the baseline score of 3 applies.

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 clear, specific purpose: answer factual questions about current or historical real-world data by routing to one of 5,724 verified-source tools and returning cited structured answers. It explicitly differentiates itself from ask_pipeworx_grounded and deep_research, so an agent can tell it apart from key 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?

Usage guidance is explicit and actionable: it tells the agent to prefer this tool over web search, provides trigger phrases like 'what is', 'look up', and 'get the latest', gives concrete example queries, and names the exact alternatives for when to step up, including ask_pipeworx_grounded and deep_research. It even clarifies how news queries should be handled.

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