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

Annotations already cover read-only, idempotent, open-world, and non-destructive behavior. The description adds useful behavioral context: it routes to the right sub-tool, fills arguments automatically, returns structured answers with stable citation URIs, and is a single fast call. It does not detail failure modes or rate limits, but the annotation safety profile lowers the 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 long but every sentence earns its place: it front-loads the primary directive, gives trigger phrases, provides six concrete examples, and includes step-up routing to siblings. The structure moves from priority claim to scope to invocation guidance to alternatives, making it easy for an agent to act on.

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 one-required-parameter default tool, the description is nearly complete: it explains what kinds of questions to send, what the tool does internally, what output shape to expect (structured answer + citation URIs), and when to escalate to siblings. It stops short of describing error/fallback behavior for unsupported questions, which would make it fully complete.

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 one meaningful parameter and its aliases at 100% coverage, so the baseline is 3. The description adds real meaning beyond the schema by defining the acceptable semantic scope: factual questions about real-world entities, events, numbers, and authoritative structured data, plus concrete example phrasings that an agent can pattern-match.

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 clearly identifies a specific verb ('routes'), a resource (5,743 tools across 1,500 verified sources), and a result (structured answer with pipeworx:// citation URIs). It distinguishes itself from web search and from siblings like ask_pipeworx_grounded and deep_research by positioning itself as the default entry point.

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 when-to-use guidance: 'PREFER OVER WEB SEARCH', 'Use whenever the user asks...', and 'START HERE for most questions'. It also names alternatives and exact step-up conditions: ask_pipeworx_grounded for hallucination-resistant single answers, and deep_research for broad/multi-part questions.

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