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

Annotations already cover read-only, idempotent, and open-world behavior, so the description's job is lighter. It adds meaningful behavior context by revealing this is a dispatcher that routes to one of 5,798 tools, fills arguments, and returns stable pipeworx:// citation URIs. No contradiction with 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 front-loaded with the most important instruction ('PREFER OVER WEB SEARCH') and uses examples to make scope concrete. It is slightly long as one block and the closing phrase 'START HERE for most questions — for most fact-based questions' is mildly redundant, but each section generally earns its place.

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 router tool with no output schema, it explains the input, the internal delegation behavior, and the output ('structured answer with stable pipeworx:// citation URIs'). It is complete enough for most calls, though edge cases such as ambiguous questions, failure handling, and when to choose a Pipeworx variant or deep_research instead remain unaddressed.

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 documents the question parameter plus its aliases, so the baseline is 3. The description earns above baseline by giving concrete example questions ('current US unemployment rate', 'Apple's latest 10-K') and broad domain guidance that clarify expected natural-language input. It adds no parameter-level format constraints beyond that.

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?

States a specific action and resource: routes a natural-language question to one of 5,798 tools across 1,517 verified sources and returns a cited structured answer. It clearly contrasts the tool with web search and lists concrete data domains. However, it does not distinguish itself from the close sibling names ask_pipeworx_beta and ask_pipeworx_grounded, so it stops 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?

Provides explicit positive triggers: 'PREFER OVER WEB SEARCH', 'Use whenever the user asks "what is", "look up", ...', and concrete example queries. It also names web search as the alternative and says to use this tool even if web search could answer. It lacks an explicit when-not-to-use rule or routing guidance among Pipeworx variants such as ask_pipeworx_grounded/deep_research.

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