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

Beyond the readOnly/idempotent annotations, the description adds useful behavioral context: the tool routes to relevant tools, fills in arguments automatically, and returns structured answers with stable pipeworx:// citation URIs. It does not mention failure modes, but the annotations already cover the safety profile.

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 key directive and organized by use case, mechanism, trigger phrases, and examples. It is somewhat long and repeats the 'use this first' idea at the end, but nearly every sentence adds useful guidance.

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 single-required-parameter tool with no output schema, the description covers what the tool does, when to use it, what kinds of questions are valid, and what the return value looks like (structured answer plus citation URIs). Explicit guidance for sibling selection, especially deep_research, 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?

Schema description coverage is 100%, and the schema already documents the question parameter and its aliases. The description provides helpful example queries and categories, but it does not add new parameter-level semantics beyond what the schema already conveys.

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 states that the tool routes a natural-language question to one of 5,743 data tools, fills arguments, and returns a structured answer with citation URIs. The scope is specific, but it does not distinguish itself from sibling tools like ask_pipeworx_beta, ask_pipeworx_grounded, or deep_research, so it stops short of a 5.

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 gives explicit when-to-use guidance: 'PREFER OVER WEB SEARCH', trigger phrases like 'what is', 'look up', 'find', and 'START HERE for most questions'. However, it does not state when not to use it or how to choose between the ask_pipeworx variants and deep_research, so exclusionary guidance is missing.

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