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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds behavioral context about routing to internal tools, filling arguments, and returning stable pipeworx:// citation URIs. It does not mention failure modes or rate limits, but this is not required given the strong annotation coverage.

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 main instruction and contains useful specifics, but it is lengthy due to multiple overlapping lists of domains, trigger phrases, and examples. The apparent duplicate 'START HERE for most questions' trailing passage adds redundancy. Overall it is acceptable but not tightly edited.

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 required parameter, no output schema, and rich annotations, the description covers behavior, scope, usage guidance, and return format. It explains that the answer is structured and includes stable citation URIs. It lacks explicit fallback or limitation guidance, but the tool's simplicity and annotation coverage make the description substantially 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 input schema already documents the question parameter and its aliases with 100% coverage. The description supplements this by providing example queries and the kinds of phrasing expected, which helps an agent formulate the argument correctly. The examples add practical meaning beyond the schema's simple 'natural language' description.

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 the tool as a natural-language router that sends questions to the right one of 5,798 tools and returns a structured answer with citations. It states the resource and scope explicitly with domain examples. It does not differentiate from sibling tools like ask_pipeworx_beta or ask_pipeworx_grounded, so it misses full sibling distinction.

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 explicitly says to prefer this over web search for factual, current, or historical questions, and lists trigger phrases and concrete examples such as 'current US unemployment rate'. It also says 'START HERE for most questions.' It does not discuss when to choose sibling research or query tools, but the primary alternative (web search) is clearly directed.

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