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

Annotations already cover the safety profile (readOnly, openWorld, idempotent, non-destructive). The description adds meaningful behavioral context beyond that: it fills arguments automatically, returns stable pipeworx:// citation URIs, works on every tier, and routes live news via news packs. There is no contradiction with annotations. A small gap is that it doesn't mention behavior for unmatched questions or possible follow-up clarifications.

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: the primary purpose and 'prefer over web search' directive come first, followed by examples and escalation paths. Some sentences lean promotional ('works on every tier, one fast call') and could be trimmed, but the structure moves logically from purpose to usage to alternatives, and every section adds useful 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?

No output schema is provided, so the description earns credit for stating the return format: 'structured answer with stable pipeworx:// citation URIs.' It covers how to use it, when to step up to alternatives, and that it handles a wide range of factual queries. It doesn't address edge cases like ambiguous questions or failure behavior, but for a broad router tool this is sufficiently complete.

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 schema already documents the required 'question' parameter and its aliases (q, text, input, query, prompt) with clear descriptions. The description adds example phrasings but doesn't introduce substantive parameter semantics beyond what the schema provides. Baseline 3 is appropriate.

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 is explicit: it routes factual questions to one of 5,724 tools across 1,497 verified sources and returns structured answers with citation URIs. It clearly positions itself as the default entry point and distinguishes itself from siblings like ask_pipeworx_grounded and deep_research. The resource and verb are concrete ('routes', 'returns structured answer'), leaving no ambiguity about what the tool does.

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?

Provides explicit when-to-use guidance: 'PREFER OVER WEB SEARCH' for specific data categories, trigger phrases like 'what is', 'look up', 'find', and concrete examples. It also gives step-up rules for alternatives (ask_pipeworx_grounded for hallucination-resistant verbatim evidence, deep_research for broad/multi-part questions) and clarifies that breaking news is already covered. This is model guidance for tool selection.

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