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

Beyond the benign readOnly/openWorld/idempotent annotations, the description reveals the essential behavior: the tool is a dispatcher that routes to the correct underlying source, fills arguments automatically, and returns structured answers with stable citation URIs. There is no contradiction with the annotations, and no important behavioral surprise is left undisclosed.

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 longer than average but each segment adds information: routing behavior, domain coverage, example queries, and sibling alternatives. It is front-loaded with the most important preference over web search, though a few phrases are redundant, such as 'even if web search could also answer it' restating 'PREFER OVER WEB SEARCH'.

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 natural-language parameter and no output schema, the description is complete: it explains what input is expected, what the tool does internally, what the output looks like with structured answer and citation URIs, and when to pick a different sibling. An agent has enough context to select and invoke this 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?

Schema coverage is 100% and the question parameter is already documented as a natural-language request with aliases, so the baseline is 3. The description adds useful parameter-level context beyond the schema through many real-world example questions and phrase triggers, showing the breadth and expected form of the requested query.

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 states a specific, differentiated behavior: ask_pipeworx routes a natural-language question to the right tool among 5,798 tools across 1,517 sources, fills arguments, and returns a structured answer with pipeworx:// citations. It is clearly distinguished from sibling tools like ask_pipeworx_grounded and deep_research, so an agent can tell what this tool does and is not.

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 prefer this tool over web search, provides trigger phrases like 'what is', 'look up', 'find', 'get the latest', 'how much', and 'current', and gives concrete example questions. It also gives exclusions and alternatives, directing memory/context queries to recall/remember, hallucination-resistant single answers to ask_pipeworx_grounded, and broad multi-part questions to deep_research.

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