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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. The description adds meaningful context by explaining that the tool routes questions across 5,798 tools and 1,517 verified sources, fills arguments, and returns structured answers with citation URIs. It does not contradict the annotations. Minor gap: it does not describe failure behavior or citation format details, but the routing and sourcing behavior is well disclosed.

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 fairly long and front-loaded with the key preference instruction, then rich examples, but it ends with a long, run-on 'packs' sentence that adds a playful rhyme but little functional clarity. The core guidance is valuable, but the final sentence is over-stuffed and hard to parse, reducing conciseness.

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 retrieval/routing tool with no output schema, the description tells the agent what it does, when to use it, what it accepts, and what the output contains (structured answer with stable citation URIs). It covers the key decisions: when to call vs web search, what question types are suitable, and example usage. It lacks detail on citation format or error handling, but for this tool's simplicity those are optional rather than essential.

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%, with the main `question` parameter thoroughly described and aliases documented. The description adds semantic value by clarifying the expected input style (natural language, open-ended factual questions), including examples. It goes beyond the schema's bare 'Your question or request in natural language' by specifying what kinds of questions work best and that the tool fills arguments automatically.

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 clearly states a specific verb and resource: it routes questions to one of many tools/sources and returns structured answers with citations. It explicitly distinguishes itself from web search and lists concrete domains and example queries, making its purpose highly identifiable.

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 gives explicit when-to-use guidance: prefer over web search for current/historical factual data, use for 'what is', 'look up', 'find', 'get the latest', etc. It also states 'START HERE for most questions', providing a clear decision rule. It doesn't enumerate alternatives, but it directly addresses the main alternative (web search) and gives strong use-case heuristics.

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