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. The description adds useful behavioral context beyond that: it routes among thousands of sources, fills tool arguments automatically, returns structured answers with stable pipeworx:// citations, and works on every tier in one fast call. It stops short of describing failure modes or citation format details, but the core 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 longer than a typical tool description but every major section earns its place: routing preference, alternatives, trigger phrases, examples, and a call-to-action. It is slightly repetitive between 'PREFER OVER WEB SEARCH' and 'START HERE for most questions', but front-loading the key guidance is effective.

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 low-parameter, annotation-rich tool, the description covers what an agent needs: when to invoke it, how to phrase the question, what happens internally, what the response includes, and how to choose alternatives. No output schema exists, but the description explicitly states that the result is a structured answer with citation URIs, which is sufficient for selection and 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?

Schema coverage is 100% and all six parameters are documented aliases for the same natural-language question, so the schema already carries most of the burden. The description adds value beyond the schema by telling the agent what kinds of phrasings and trigger words map well to this tool, such as 'look up', 'find', 'get the latest', and 'current'.

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 behavior: routes natural-language questions to the appropriate one of 5,743 tools and returns structured answers with citation URIs. It differentiates itself from siblings by explicitly naming ask_pipeworx_grounded and deep_research as alternatives for different use cases.

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?

The description is explicit about when to use this tool versus alternatives: prefer it over web search for factual/structured-data questions, use ask_pipeworx_grounded for hallucination-resistant answers with verbatim evidence, and use deep_research for broad/multi-part questions. It also gives trigger phrases and concrete examples, leaving little to inference.

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