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

Annotations already cover read-only, idempotent, open-world, and non-destructive behavior. The description adds valuable context beyond this: it routes across 5,743 tools, returns structured answers with stable citation URIs, works on every tier, and is a single fast call. This extra behavioral information (routing mechanism, performance, tier compatibility) helps the agent set expectations without contradicting 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 long but highly structured and front-loaded with the key directive ('PREFER OVER WEB SEARCH'). It uses clear sections, bold cues, and examples. While every sentence earns its place, some redundancy exists (repeating domain lists and triggers). Still, it's efficient for its breadth and purpose.

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?

Given no output schema, the description adequately explains what is returned (structured answer with citation URIs). It covers scope, usage triggers, examples, and sibling differentiations. Missing details like error behavior or response format specifics are minor, and the tool's broad nature makes full completeness impractical. It is sufficiently complete for a caller to decide and invoke 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 description coverage is 100%, with aliases for the 'question' parameter fully documented. The description does not enrich parameter semantics beyond noting natural language and providing examples, which is helpful but does not compensate for what the schema already explains. Baseline 3 is appropriate since nothing is missing.

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 purpose: routing factual questions to appropriate data sources and returning structured answers with citation URIs. It explicitly lists the domains covered and differentiates itself from siblings like ask_pipeworx_grounded and deep_research, making its role unambiguous.

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 factual questions about real-world entities) and when-not-to-use conditions (use ask_pipeworx_grounded for hallucination-resistance, deep_research for broad multi-part questions). It even includes trigger phrases and examples, leaving no ambiguity about when to invoke this tool.

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