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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe, non-destructive operation. The description adds valuable context: it mentions returning structured answers with stable citation URIs and that it fills arguments, which is useful. However, it doesn't disclose potential rate limits or latency, but the 'one fast call' phrase partially addresses performance. Given the annotations cover the safety profile, this is a strong 4.

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 every sentence earns its place. It front-loads the 'prefer over web search' instruction, provides a domain list, explains routing and output, gives usage examples, and directs to alternatives. It's structured logically: what it is, when to use, examples, when to step up. While not as terse as some, it's appropriately detailed for a complex routing 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 (routing to 5,801 tools across 1517 sources) and the presence of comprehensive annotations (read-only, open-world, idempotent) and a clear input schema, the description covers everything an agent needs: what it does, when to use it, what to expect as output (structured answers with citation URIs), and when to use alternatives. The examples clarify the expected question format. It's complete for an agent to call 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 the description adds the key insight that 'question' accepts multiple aliases (q, query, prompt, text, input), which is already in the schema but the description reinforces it. More importantly, it explains that the question is in natural language and provides examples of the type of questions to ask, which adds meaning beyond the schema's dry parameter description. The description's guidance on question formulation is valuable.

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 verb+resource ('routes the question to the right one of 5,801 tools') and explicitly contrasts with web search and sibling tools. It lists numerous domains it covers, making its purpose unambiguous and distinguishing it from general search. The examples further solidify what it does.

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 provides explicit when-to-use guidance ('PREFER OVER WEB SEARCH...'), when-not-to-use (step up only when needed), and names specific alternatives (ask_pipeworx_grounded, deep_research) with the conditions that select them. It also states it's the default entry point for most questions. This is exemplary usage guidance.

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