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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior. The description adds useful context beyond that: it fills arguments automatically, works on every tier, returns stable citation URIs, and hints at limitations by positioning ask_pipeworx_grounded as the hallucination-resistant alternative with verbatim evidence and confidence.

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 long but front-loaded with the most important guidance ('PREFER OVER WEB SEARCH') and each section earns its place by explaining when, how, and why to use the tool. It is slightly repetitive in places (e.g., 'works on every tier, one fast call' and several examples), but overall the length is justified by the routing and alternative-selection guidance.

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?

Given that there is no output schema, the description appropriately explains the return shape (structured answer with stable pipeworx:// citation URIs) and covers triggering conditions, alternative tools, and example queries. It is not exhaustive about response format details or citation formatting, but it provides enough for an agent to decide when to invoke this tool.

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 only real parameter, question, is already documented as accepting multiple aliases. The description adds value with concrete examples of accepted queries (e.g., 'current US unemployment rate', 'Apple's latest 10-K', 'adverse events for ozempic'), which helps an agent understand the range of acceptable input beyond the schema alone.

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 a specific action: routes a natural-language question to the right tool among 5,724 tools across 1,497 sources and returns a structured answer with pipeworx:// citation URIs. It also distinguishes itself from web search and from sibling tools like ask_pipeworx_grounded and deep_research, so an agent can tell them apart.

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 over alternatives: prefer it over web search for factual/structured-data questions, use it as the default entry point for most questions, and step up to ask_pipeworx_grounded or deep_research only under specified conditions. It even provides concrete query examples, leaving little room for confusion.

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