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

With annotations already marking the tool as read-only, open-world, idempotent, and non-destructive, the description adds meaningful behavioral context: it auto-routes to the appropriate underlying tool, fills required arguments, and returns structured answers with stable pipeworx:// citation URIs. This sets correct agent expectations about indirection, citation format, and the breadth of data sources. There is no contradiction with 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 content is front-loaded with the most important instruction, but the description repeats a nearly identical multi-sentence block a second time, which wastes tokens and violates the principle that every sentence should earn its place. The examples, domain list, and exclusions are valuable, but the duplication makes the description unnecessarily bloated.

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 tool with a single semantic parameter and no output schema, the description is unusually complete: it covers when to use it, what kinds of questions it handles, real examples, explicit exclusions, and the citation-bearing return format. It is slightly incomplete in not differentiating ask_pipeworx from its grounded/beta siblings, but overall an agent has enough context to invoke it correctly in most cases.

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 the schema already explains that 'question' is a natural-language request and that q, text, input, query, and prompt are aliases. The description reinforces that the input is a question, but it adds no parameter-level detail beyond what the schema already provides, 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 states what the tool does: it takes a natural-language question and routes it to one of 5,798 tools across 1,517 verified sources, filling arguments and returning a structured answer with citation URIs. It also distinguishes itself from plain web search by enumerating concrete domains like SEC filings, FDA data, FRED/BLS statistics, patents, and real estate. This is specific, actionable, and far beyond a tautology.

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 gives explicit usage guidance: prefer this over web search for factual questions about real-world data, use it when the user asks 'what is', 'look up', 'find', 'get the latest', or 'how much', and it even includes worked examples. It also lists exclusions such as meta-questions about Pipeworx itself, opinions, math, code generation, and personal advice. However, it does not mention sibling tools like ask_pipeworx_beta or ask_pipeworx_grounded, so the agent is not told when to choose those alternatives instead.

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