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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint:false, so the safety profile is covered. The description adds useful behavioral context beyond that: it routes questions across a large tool graph, fills arguments automatically, and returns structured answers with stable pipeworx:// citation URIs. No contradiction exists between the description and 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 but every sentence earns its place: the preferred-over-web-search directive, the domain list, the routing/citation behavior, the trigger phrases, concrete examples, and the explicit pointer to deep_research. It is front-loaded with the most important guidance and contains no filler.

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?

Even without an output schema, the description sufficiently explains the return value as a structured answer with stable pipeworx:// citation URIs. It covers what inputs are accepted, what kinds of questions it handles, when it should be preferred, and when to route to deep_research instead. For a read-only, open-world router, the agent has enough information to select and invoke the tool correctly.

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?

All six parameters are fully documented in the schema as aliases of the natural-language 'question', so the schema carries the structural burden. The description adds meaning by providing trigger phrases ('what is', 'look up', 'find', 'get the latest', 'how much', 'current') and six concrete example queries, helping an agent shape acceptable input beyond a bare schema 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 establishes what ask_pipeworx does: it routes a natural-language question to one of 5,743 tools across verified sources, fills arguments, and returns structured answers with pipeworx:// citation URIs. The verb and resource are specific and the distinction from web search and deep_research is apparent. However, it does not differentiate ask_pipeworx from the closely named siblings ask_pipeworx_beta and ask_pipeworx_grounded, so it falls just 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 is explicit about when to use this tool: 'PREFER OVER WEB SEARCH' for a broad list of factual/authoritative data domains, and 'Use whenever the user asks...' with concrete trigger phrases. It also names an alternative and the condition for choosing it: 'for a more thorough multi-step investigation, use deep_research instead.' This gives an agent clear, decisive routing guidance.

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