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

Annotations already establish readOnly, openWorld, and idempotent behavior, and the description adds useful context beyond them: it routes to sub-tools, fills arguments, returns citation URIs, works on every tier, is one fast call, and handles live news routing. Nothing in the description contradicts the 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 dense and front-loaded with the key decision guidance, and it uses examples and alternatives effectively. It has minor redundancy, such as restating the preference over web search and repeating 'START HERE,' but overall every major section contributes useful information.

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?

Given no output schema, the description still explains what the tool returns, what sources it covers, what kinds of questions it handles, and when to choose a different sibling tool. It is sufficiently complete for an agent to select and invoke the tool correctly without additional inference.

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 parameter aliases are already well documented. The description adds value by clarifying the semantic range of acceptable questions, providing trigger phrases, and giving concrete examples of valid queries like 'current US unemployment rate' and 'Apple's latest 10-K.' That goes beyond the schema 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 states a specific action: routes a natural-language question to the right tool among 5,798 tools across 1,517 verified sources and returns a structured answer with stable pipeworx:// citation URIs. It clearly distinguishes itself from web search and from siblings like ask_pipeworx_grounded and deep_research.

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 to prefer this over web search, gives trigger phrases and examples, and says 'START HERE for most questions.' It also names the exact conditions for stepping up to ask_pipeworx_grounded or deep_research, making when-to-use versus alternatives unambiguous.

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