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

Given annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, the description goes beyond these by explaining that the tool routes to the right internal tool, fills arguments, and returns an answer with pipeworx:// citation URIs. This is useful behavioral context, especially since there is no output schema. It does not mention potential latency or failure modes, but the core behavior is transparent.

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 a key usage directive and includes a useful list of domains and examples. Some repetition exists ('PREFER OVER WEB SEARCH' appears at both start and end), but every section contributes to the agent's decision-making.

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 is largely complete for a tool of this complexity: it explains what it does, when to use it, what it returns, and gives examples. Since there is no output schema, the mention of structured answers and citation URIs is valuable. It does not cover every possible edge case, but is sufficient for correct selection and invocation.

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 covers all six parameters and describes them as aliases for a single natural-language question, so the schema already provides strong coverage. The description adds meaningful semantics by specifying the types of factual questions to ask and providing examples, which helps the agent understand what input 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 states that ask_pipeworx routes natural-language questions to one of thousands of tools across verified sources and returns structured answers with citation URIs. It is specific about the resource and function. However, it does not distinguish itself from sibling tools like ask_pipeworx_beta or ask_pipeworx_grounded, so it falls short of full sibling differentiation.

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 provides explicit when-to-use guidance, including a strong directive to prefer it over web search, a detailed list of domains, and concrete example queries. It gives clear context and even says 'START HERE for most questions.' However, it does not provide explicit when-not-to-use guidance or compare itself to sibling ask_pipeworx variants.

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