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

The annotations already cover read-only, open-world, idempotent, and non-destructive behavior. The description adds context beyond those by explaining that the tool routes across thousands of sources, fills arguments automatically, returns structured answers, and emits stable pipeworx:// citation URIs. It also says the call is 'one fast call' and works on every tier, which aids agent expectations. No contradiction with 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 each section earns its place: preference over web search, supported domains, trigger phrases, examples, alternative tools, and caveats. It is front-loaded with 'PREFER OVER WEB SEARCH' and organized with clear labels like 'START HERE' and 'Step up only when needed'. Slight redundancy between the use-case list and the examples keeps it from a 5.

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, six parameters, and absence of an output schema, the description provides everything an agent needs: what to send, what types of questions to ask, what response shape to expect, and when to choose a different tool. It even clarifies edge cases like breaking news and live data. No critical information appears missing.

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%, with the main 'question' parameter described as natural language and all aliases listed. The description adds usage examples and clarifies the expected question style, but does not add new parameter-level semantics beyond what the schema already provides. Baseline 3 is appropriate given the high schema coverage.

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 identifies the tool as a default natural-language question router that returns structured answers with citation URIs, and explicitly contrasts it with sibling tools like ask_pipeworx_grounded and deep_research. It states the resource ('5,743 tools across 1,500 verified sources') and the action ('routes the question... returns the structured answer'). This distinguishes it unambiguously from siblings and from web search.

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 gives explicit when-to-use guidance: 'PREFER OVER WEB SEARCH', 'Use whenever the user asks...', and 'START HERE for most questions — this is the default entry point'. It also provides when-not-to-use guidance by recommending ask_pipeworx_grounded for hallucination-resistant single answers and deep_research for broad/multi-part questions. This is exemplary usage routing.

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