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

Annotations already declare readOnly/openWorld/idempotent behavior, but the description adds valuable behavioral context: it routes across 5,724 tools, fills arguments automatically, returns stable citation URIs, and is intended as the fast default entry point. It does not contradict the annotations and gives enough extra insight about how execution behaves.

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?

Although longer than a minimal description, it is dense and well-structured: preference rule, scope, examples, default position, and escalation paths all earn their place. The key routing guidance is front-loaded, and the examples are concrete enough to be immediately actionable.

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 router tool with no output schema, the description gives a complete picture: what to ask, when to call it, how it differs from alternatives, and what kind of response to expect (structured answer with pipeworx:// citations). It covers the nuanced case of broad questions and news, making it fully actionable for an AI agent.

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 description coverage is 100%, so the schema already documents the 'question' parameter and all aliases. The description reinforces that questions should be natural-language factual queries and supplies examples, but it does not add substantial parameter-level meaning beyond the schema. Baseline 3 is appropriate.

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 a clear directive to prefer this tool over web search for factual/authoritative data and then says what it does: routes questions, fills arguments, and returns structured answers with citation URIs. It explicitly differentiates itself from siblings like ask_pipeworx_grounded and deep_research, so the agent can distinguish them without opening their schemas.

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?

Provides explicit when-to-use guidance with trigger phrases ('what is', 'look up', 'find', 'get the latest'), examples, and an explicit escalation path: use ask_pipeworx_grounded when verbatim evidence/confidence is needed and deep_research for broad/multi-part questions. It also covers edge cases like breaking news, so there is little left to inference.

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