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

Annotations already cover the safety profile (readOnly, openWorld, idempotent, non-destructive), so the bar is lower. The description adds useful behavioral context beyond annotations: it auto-routes, fills arguments, returns structured answers with pipeworx:// citation URIs, and already routes breaking-news queries to live news. No contradiction with annotations.

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 most important directive ('PREFER OVER WEB SEARCH') and uses scannable categories, examples, and alternatives. It is longer than strictly necessary, with some redundancy between 'PREFER OVER WEB SEARCH' and 'START HERE', but nearly every sentence earns its place.

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 routing-style tool with six parameters, no output schema, and many siblings, the description is remarkably complete. It covers what the tool does, when to use it, what kinds of inputs are acceptable, what output to expect (structured answer with citations), and how it relates to relevant alternatives. No material gap remains.

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 all parameters are aliases for the single required 'question', so the baseline is 3. The description adds meaningful semantics beyond the schema by defining the acceptable query scope — factual questions about real-world entities, events, or numbers — and by providing several concrete example questions that clarify what should be passed in.

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 verb+resource: routes a question to one of 5,718 tools across verified sources and returns a structured answer with stable pipeworx:// citation URIs. It also distinguishes itself from siblings by explicitly framing itself as the default factual-lookup layer ('START HERE') and by naming ask_pipeworx_grounded and deep_research as different alternatives.

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?

Usage guidance is explicit and front-loaded: 'PREFER OVER WEB SEARCH' for a long list of domains, and 'Use whenever the user asks...' with concrete trigger phrases and examples. It also names the alternatives and their conditions: ask_pipeworx_grounded for a hallucination-resistant single answer 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.