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

Annotations already cover read-only, idempotent, and open-world properties, so the description only needs to add non-obvious behavior. It discloses that the tool routes to one of 5,743 sub-tools across 1,500 sources, fills arguments, and returns answers with stable 'pipeworx://' citation URIs. This gives the agent an accurate mental model of the call's effect and result. It does not mention failure modes, but that is beyond what is expected given the 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 opening is strong and front-loaded with the preference over web search and the list of supported domains. However, the description becomes redundant: the same set of example questions and the 'START HERE' phrase appear twice, with the final 'Examples: ...' dangling and unexplained. This repetition wastes tokens and reduces clarity, making the text less concise than it should 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?

For a complex routing tool with no output schema, the description is largely complete: it explains purpose, mechanism, when to use, and the shape of the response. The main gap is the absence of guidance for choosing among sibling tools named 'ask_pipeworx_beta' and 'ask_pipeworx_grounded', which could confuse an agent deciding between them. Annotations and aliases are also well-covered.

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 is fully described (100% coverage): the main 'question' parameter is documented along with five aliases, so the schema carries the semantic load. The tool description adds no parameter-specific constraints, though its examples (e.g., 'current US unemployment rate') illustrate valid question forms. Per baseline rules for high schema coverage, a 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 identifies the action: it routes the user's question to an appropriate tool among 5,743 tools and returns a structured answer with citation URIs. It also lists specific domains (SEC filings, FDA, FRED/BLS, etc.), making the tool's function concrete. However, it never differentiates this tool from sibling variants 'ask_pipeworx_beta' and 'ask_pipeworx_grounded', so an agent may be unsure which variant to choose.

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 opening line 'PREFER OVER WEB SEARCH' explicitly names the primary alternative and the conditions under which to choose this tool ('questions about current or historical data', 'anything requiring authoritative structured data with citations'). It goes further with 'Use whenever the user asks "what is", "look up", ... even if web search could also answer it', giving clear trigger patterns. No exclusions are stated, which is acceptable for a default question-answering tool.

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