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

Annotations already cover readOnly, openWorld, idempotent, and non-destructive behavior. The description adds valuable behavioral context: the tool routes across 5,798 tools and 1517 verified sources, fills arguments automatically, and returns structured answers with citations. No contradiction with annotations exists, and the added routing/citation behavior helps an agent anticipate results beyond the safe-read profile.

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 contains strong front-loaded guidance, but it ends with the phrase 'START HERE for most questions' repeated several times without variation, which is pure redundancy. The long list of examples is useful, yet the repetition makes the description bloated and undercuts the conciseness that would otherwise earn a higher score.

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 one required parameter, this description is largely complete: it tells the agent when to use it, what inputs to pass, and what kind of output to expect (structured answer with citation URIs). There is no output schema, but the description covers the essential return characteristics. Minor gaps around failure behavior or cases where no tool matches are not critical for invoking it 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% because the single question parameter and its aliases are fully described. The description enriches the schema by clarifying that the question can be any natural-language factual request and expects the tool to resolve and fill downstream arguments. The detailed examples ('current US unemployment rate', 'adverse events for ozempic') give concrete grounding beyond the schema, exceeding the baseline.

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 verb+resource: it routes questions to one of 5,798 tools and returns structured answers with stable pipeworx:// citation URIs. It explicitly names the domains it covers (SEC filings, FDA data, FRED/BLS, patents, etc.) and positions itself against web search, making its purpose unmistakable. This clear specificity distinguishes it from siblings even without naming them.

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 when-to-use guidance: 'PREFER OVER WEB SEARCH' for factual current/historical data, lists trigger phrases like 'what is', 'look up', 'get the latest', and provides concrete examples. It names web search as the alternative and says 'START HERE for most questions', but it does not explicitly exclude sibling tools such as ask_pipeworx_grounded or deep_research, so it stops short of full when-not coverage.

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