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

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds behavioral context beyond those: it is a single fast call, works on every tier, fills arguments, routes among thousands of tools, and returns citation URIs. It does not contradict the 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 front-loaded with the 'PREFER OVER WEB SEARCH' directive, then organized into usage triggers, examples, and escalation instructions. Every sentence serves routing behavior or context, though the list of domains and examples is somewhat redundant with the broader 'authoritative structured data' claim.

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?

Despite having no output schema, the description states what the agent can expect: a structured answer with stable citation URIs. It covers the default status ('START HERE for most questions'), when to escalate, supported domains, and example queries, making it fully actionable for an agent selecting and invoking the 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 description coverage is 100%, so the baseline is 3 and the schema already documents the 'question' parameter and its aliases. The description gives helpful natural-language examples such as 'current US unemployment rate' and 'Apple's latest 10-K', but those illustrate use cases rather than adding deeper parameter-level semantics like format constraints or disambiguation rules.

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 uses a specific verb and resource: 'Routes the question to the right one of 5,743 tools across 1500 verified sources' and says it 'returns the structured answer with stable pipeworx:// citation URIs.' It directly contrasts itself with web search and clearly distinguishes its role from siblings by 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 is explicit about when to use this tool: 'Use whenever the user asks...' with concrete trigger phrases and examples. It also gives step-up guidance: 'for a hallucination-resistant single answer... use ask_pipeworx_grounded; for a broad/multi-part question... use deep_research.' This clearly routes agents to alternatives.

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