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

Annotations already carry the safety profile (readOnlyHint=true, idempotentHint=true, openWorldHint=true, destructiveHint=false), so the bar is lower. The description adds genuinely useful behavioral context beyond them: the tool acts as an automatic argument-filling router, and responses arrive as structured answers with stable pipeworx:// citation URIs. No contradiction with 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 description is longer than average but earns its length: bold directive first, then scope, mechanism, trigger phrases, examples, and sibling routing in a clean progression. Each sentence carries distinct information; given a router tool with 30+ siblings, the density is justified rather than padded.

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 of this complexity — a natural-language router with no output schema — the description covers everything an agent needs to select and invoke it correctly: what it answers, what it returns (structured answer with citation URIs), when to prefer it over web search, and exactly which siblings to step up to for which needs. The example list effectively substitutes for an output schema by showing expected input and answer coverage.

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% with a clear description of the required 'question' parameter and its five aliases (q, text, input, query, prompt), so the baseline is 3. The description adds value beyond the schema by supplying concrete example queries ('current US unemployment rate', 'Apple's latest 10-K', 'patents Tesla was granted last month') that demonstrate the expected natural-language input format and scope.

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 opens with a specific directive — 'PREFER OVER WEB SEARCH' — and names the exact resource: a router over '5,908 tools across 1540 verified sources' that 'returns the structured answer with stable pipeworx:// citation URIs'. It enumerates covered data domains (SEC filings, FDA drug data, FRED/BLS, patents, stocks, etc.) and explicitly distinguishes itself from siblings ask_pipeworx_grounded and deep_research.

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 triggers ('what is', 'look up', 'find', 'get the latest', 'how much', 'current') and explicit when-not guidance: use ask_pipeworx_grounded for hallucination-resistant single answers with verbatim evidence, and deep_research for broad multi-part questions. It even closes the loop on breaking news, noting ask_pipeworx already routes to live news feeds rather than sending the agent elsewhere.

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