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

Annotations already mark it read-only, idempotent, and non-destructive. The description adds meaningful context beyond that: it routes to one of 5,743 tools, fills arguments, returns structured answers with stable pipeworx:// citation URIs, and works as a fast single call. It does not fully disclose failure modes or rate limits, but those are less critical given the annotation coverage.

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 front-loaded with the most important directive ('PREFER OVER WEB SEARCH') and organized into clear usage guidance, examples, and escalation paths. Some repetition exists, but each block earns its place by answering likely agent decision questions.

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?

With no output schema present, the description adequately describes the return shape: structured answer with stable citation URIs. It covers scope, examples, alternatives, the default entry point, and breaking-news behavior. An agent has everything needed to decide when and how to invoke this tool.

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 already documents the single required 'question' parameter and its aliases at 100% coverage. The description adds value by providing concrete example queries ('current US unemployment rate', 'Apple's latest 10-K') and clarifying that the parameter accepts natural language, going beyond the schema's generic field description.

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 specific action: routing a question to the right tool from 5,743 tools and returning a structured answer with citations. It clearly distinguishes itself from web search and sibling tools like ask_pipeworx_grounded and deep_research. The scope of supported data domains is explicit and actionable.

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 guidance on when to prefer this tool over web search and when to step up to alternatives: ask_pipeworx_grounded for hallucination-resistant single answers with verbatim evidence, and deep_research for broad/multi-part questions. It also marks itself as the default entry point, leaving no doubt about routing decisions.

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