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

Annotations already declare readOnly, open-world, and idempotent hints, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations: it routes to 5,724 tools, fills arguments, returns citation URIs, works on every tier, and is a fast default call. It doesn't 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 well-structured and front-loaded with the most important guidance. Examples and use-case lists are valuable for an agent. Minor redundancy exists between 'PREFER OVER WEB SEARCH' and later 'Use whenever...' phrasing, but nothing is filler.

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 the tool's broad scope, the description is remarkably complete: it explains what the tool does, when to use it, which alternatives to step up to, how answers are returned, and that it works on every tier. Even without an output schema, it conveys the return format (structured answer with pipeworx:// citation URIs) and enough examples to invoke it 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 the 'question' parameter described and aliases documented. The tool description adds examples and trigger phrases that help formulate a query, but it doesn't add new meaning about the parameter itself beyond what the schema already 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 clearly states what the tool does: it routes natural-language questions to the appropriate one of thousands of verified data tools and returns structured answers with citation URIs. It explicitly differentiates itself from web search and from siblings like ask_pipeworx_grounded and deep_research, so an agent can distinguish it without inspecting 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?

Provides explicit when-to-use guidance: prefer over web search for factual/current/historical data, use for trigger phrases like 'what is' and 'look up', and start here as the default entry point. It also gives clear step-up conditions for ask_pipeworx_grounded and deep_research, plus notes that breaking-news questions are already handled.

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