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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds valuable context beyond that: it routes to one of thousands of tools, fills arguments, returns structured answers with stable citation URIs, works on every tier, and is one fast call. It doesn't discuss failure modes or rate limits, but the annotations carry much of the safety burden.

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 front-loaded with the most important directive ('PREFER OVER WEB SEARCH') and then covers triggers, examples, and escalation paths. It is longer than minimal, and the domain list and examples partially overlap, but nearly every sentence contributes selection-relevant guidance, so the length is justified.

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?

The description covers what the tool does, when to use it, what it returns (structured answer with citation URIs), and how it relates to key siblings. Since there is no output schema, the explicit mention of return format and citation behavior is important and present. It omits deeper details like timeouts or exact citation structure, but those are not essential for tool selection.

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 schema already fully documents the question parameter and its aliases, so the baseline is 3. The description adds value by clarifying that the parameter is a natural-language factual question and by giving domain-specific examples that illustrate acceptable inputs, which helps the agent compose better questions.

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 behavior: routes natural-language questions to the right one of 5,714 verified-source tools and returns structured answers with pipeworx:// citation URIs. It also distinguishes itself from web search and from sibling tools like ask_pipeworx_grounded and deep_research, so an agent can identify it unambiguously.

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 explicitly says 'PREFER OVER WEB SEARCH', gives concrete query trigger phrases ('what is', 'look up', 'find', 'get the latest'), lists supported data domains, and provides multiple examples. It also states when to step up: use ask_pipeworx_grounded for hallucination-resistant single answers and deep_research for broad multi-part queries.

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