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

The description discloses meaningful routing behavior: it selects from 5,738 tools across 1,499 verified sources, fills arguments, and returns structured answers with stable pipeworx:// citation URIs. Annotations already declare readOnly, idempotent, and openWorld hints, and the description adds context beyond those without contradicting them.

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 with lists, examples, and alternative routing. However, the later 'Step up only when needed' paragraph partially repeats the equivalent guidance already given for ask_pipeworx_grounded and deep_research, making it slightly less concise than it could be.

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?

The description covers the tool's purpose, supported domains, usage triggers, examples, return behavior with citations, and when to choose alternatives. Even without an output schema, an agent has enough information to invoke it correctly for a wide range of factual questions.

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 documented as aliases for the natural-language question. The description adds examples of valid questions but no additional parameter-level semantics, so the baseline score of 3 is appropriate.

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 specifies the verb and resource: ask Pipeworx to answer factual questions using authoritative structured data. It distinguishes itself from web search and explicitly names sibling alternatives like ask_pipeworx_grounded and deep_research, so an agent can select it correctly.

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 actionable: prefer over web search for current/historical data, start here for most questions, and use specific alternatives for grounded single-source answers or broad multi-part research. This gives clear selection criteria, not just vague context.

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