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

The annotations already indicate a safe, read-only, idempotent, open-world operation, and the description adds valuable behavioral detail beyond that: it routes to one of 5,908 tools, fills arguments, and returns structured answers with stable pipeworx:// citation URIs. It also discloses that breaking-news questions are routed to live news and news-feed packs. No annotation contradiction exists.

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 every sentence earns its place: scope, mechanism, trigger phrases, examples, and sibling routing are all covered in a compact, front-loaded structure. The first line immediately tells the agent when to prefer this tool, which is ideal for selection.

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?

Even without an output schema, the description explains what the caller receives: a structured answer with stable citation URIs. It covers when to use the tool, what kinds of questions to ask, how it behaves, and which siblings to choose for specialized needs. Nothing essential for an agent to invoke it correctly appears to be missing.

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 fully documents the question parameter and its aliases (100% coverage), so the baseline is 3. The description adds value by giving concrete example inputs and by defining the acceptable scope of natural-language questions, including queries that web search could also answer. This reinforces and slightly extends the schema's bare 'natural language' 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 names a specific action and resource: asking Pipeworx a factual question and routing it to authoritative data tools. It distinguishes the tool from siblings by explicitly naming ask_pipeworx_grounded and deep_research as alternatives for different needs. The many concrete examples further clarify the exact kind of task it handles.

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 the tool: prefer it over web search, use it for factual queries about real-world data, and start here for most questions. It also names when-not conditions by directing users to ask_pipeworx_grounded for hallucination-resistant single answers and to deep_research for broad/multi-part investigations. This is unusually clear routing guidance.

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