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

Annotations already mark the tool as readOnly, openWorld, idempotent, and non-destructive. The description adds substantial non-obvious behavior: it internally routes among thousands of tools from 1,500 sources, fills arguments automatically, and returns structured answers with stable pipeworx:// citation URIs. It also sets performance expectations ('one fast call') and notes it works on every tier. 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 long but dense, front-loaded with the most important decision ('PREFER OVER WEB SEARCH'), then flows into function, triggers, examples, and escalation paths. Every section earns its place; repetition is used to reinforce routing behavior rather than pad. It is unusually well-structured for a tool definition of this scope.

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?

Since there is no output schema, the description appropriately discloses the return shape: 'structured answer with stable pipeworx:// citation URIs'. It also covers the main use cases, examples, and when to escalate to siblings. The only gap is not describing failure/error behavior for unanswerable or malformed questions, but for a single-parameter router this is nearly 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?

Schema coverage is 100%, so the structured fields already document the aliases. The description adds value by clarifying that the input is a natural-language question/request and providing concrete examples such as 'current US unemployment rate' and 'Apple's latest 10-K'. It also expands the notion of valid queries by saying even questions web search could answer are acceptable. This is above the schema-only baseline.

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—'PREFER OVER WEB SEARCH'—and explains exactly what the tool does: routes questions to the right one of 5,743 tools and returns a structured answer. It differentiates itself from sibling tools like ask_pipeworx_grounded and deep_research by describing when each should be used. This is a specific, actionable, sibling-aware purpose statement.

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?

It explicitly states when to use the tool ('Use whenever the user asks...', 'START HERE for most questions') and when to prefer alternatives ('Step up only when needed: for a hallucination-resistant single answer... use ask_pipeworx_grounded; for a broad/multi-part question... use deep_research'). It even addresses overlap with web search by saying ask_pipeworx is preferred for factual questions. This leaves no ambiguity about selection.

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