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

Annotations already carry the safety/read-only profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), so the bar is lower. The description adds meaningful behavioral context: it routes to sub-tools, fills arguments automatically, returns structured answers with stable pipeworx:// citation URIs, and claims 'works on every tier, one fast call'. This explains what happens beyond what annotations state, though it does not disclose potential failure modes or limits for out-of-scope questions.

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 purposefully dense. It front-loads the key directive ('PREFER OVER WEB SEARCH'), states the resource scope, gives concrete examples, and provides step-up guidance — every section has a distinct job. It is slightly repetitive ('any factual question... even if web search could also answer it' restates earlier points), but overall it earns its length given the tool is a general-purpose router needing to distinguish itself from siblings.

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 router tool with no output schema, the description is unusually complete: it covers target domains, example queries, return format (structured answer with citations), when to prefer it, and when to use alternatives. It does not mention edge cases such as unsupported question types or possible error behavior, but what an agent needs to call it correctly and understand its response is present.

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 description coverage is 100% — 'question' and its five aliases are already documented in the schema. The description adds illustrative example questions but no new semantics about parameter formats or constraints. Per the rubric, a baseline of 3 is appropriate when the schema does the heavy lifting, and the description does not meaningfully compensate beyond making the intended input style clearer.

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 function: route a natural-language question to the right one of 5,743 tools across 1,500 verified sources and return a structured answer with citation URIs. It lists concrete domains (SEC filings, FDA drug data, FRED/BLS, patents, etc.) and provides example questions, making the purpose unmistakable. It also distinguishes itself from siblings by naming ask_pipeworx_grounded and deep_research as alternatives, so an agent can tell them apart without opening schemas.

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?

Explicit guidance is abundant: 'PREFER OVER WEB SEARCH', 'Use whenever the user asks "what is", "look up", "find"...', and 'START HERE for most questions — this is the default entry point'. It also states when to step up to alternatives ('for a hallucination-resistant single answer... use ask_pipeworx_grounded; for a broad/multi-part question... use deep_research') and clarifies that breaking-news questions are already handled. This fully covers when to use this tool vs. the alternatives.

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