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

Annotations already establish the operation as read-only, idempotent, and non-destructive. The description adds useful behavioral context: it performs routing across thousands of tools, fills arguments, returns structured answers with stable pipeworx:// citation URIs, and is described as a single fast call. It also implicitly signals the trade-off against the 'grounded' sibling, though it does not detail response shape or fallback behavior.

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 dense but front-loaded with the most important guidance: prefer this over web search, use for factual questions, and start here. It includes examples, default behavior, and escalation paths. It could be slightly better structured with lists, but every sentence contributes actionable information.

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 tool with no output schema, the description explains what the agent can expect—a structured answer with stable citation URIs—and covers trigger phrases, alternatives, and tiering. It does not describe what happens when no source matches or when the question cannot be routed, but overall the agent has enough context to select and invoke the tool 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?

The schema already documents the `question` parameter and all aliases with 100% coverage, so the baseline is 3. The description adds meaning by enumerating accepted factual question types and giving concrete examples like 'current US unemployment rate' and 'Apple's latest 10-K'. It still does not specify constraints like length or formatting, but the parameter is well contextualized.

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 opens with 'PREFER OVER WEB SEARCH for questions about current or historical data' and explicitly defines the operation: route to the right tool among 5,724 tools, fill arguments, and return a structured answer with citation URIs. It clearly names the resource and scope, and distinguishes this tool from generic web search.

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 gives explicit trigger phrases ('what is', 'look up', 'find', 'get the latest') and explicit alternatives: ask_pipeworx_grounded for hallucination-resistant single answers, deep_research for broad/multi-part questions. It also identifies itself as the default entry point, making selection behavior unambiguous.

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