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

Annotations already claim readOnlyHint, openWorldHint, idempotentHint, non-destructive. The description adds valuable routing behavior: it fills arguments automatically, returns structured answers with stable pipeworx:// citation URIs, and covers live news routing. It doesn't mention rate limits, latency, or failure behavior, but with strong annotation coverage and explicit routing semantics, the added context is meaningful.

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 key routing instruction and compressed list of domains, then gives trigger phrases and examples, then sibling differentiation. It is long but packed with useful routing detail; each sentence earns its place. Slight redundancy between 'SEC filings, ... weather' and the later example list, but no wasted filler.

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 a single natural-language parameter, no output schema, and rich annotations, the description fully equips an agent: when to prefer it, what to expect back (structured answer with citations), and how it differs from grounded and deep research siblings. There is no missing information that would block correct invocation.

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 coverage is 100% and the `question` property is described as natural language with aliases. The description's examples ('What was Apple's revenue in 2024?', 'Any recent SEC filings for $NVDA?', 'Current price of bitcoin') add flavor but don't deeply extend schema semantics. Baseline 3 is appropriate because the schema already fully documents the single meaningful parameter.

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 verb ('ask', 'routes', 'returns') and a clear resource (Pipeworx, a gateway to 5,743 tools across 1500 verified sources). It distinguishes itself from web search and from sibling tools ask_pipeworx_grounded and deep_research by name and use case. The scope is concrete: factual questions about real-world entities, events, numbers, or data requiring citations.

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?

Explicitly says 'PREFER OVER WEB SEARCH' for a wide category of factual questions, gives trigger phrases ('what is', 'look up', 'find', 'get the latest', 'how much', 'current'), concrete examples, and names alternatives: ask_pipeworx_grounded for hallucination-resistant grounded answers, deep_research for multi-source broad questions, and live-news packs for breaking news. This is strong routing guidance.

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