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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds substantial behavioral context beyond them: it discloses that the tool routes to internal tools, fills arguments, returns citations, is a 'one fast call', 'works on every tier', and handles live news. 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 long, but it is densely informative and front-loaded with the most critical guidance ('PREFER OVER WEB SEARCH' and the routing mechanics). Every sentence contributes: domain list, trigger phrases, examples, comparisons to siblings, and breaking-news handling. Slightly verbose, but appropriately so for a default entry point.

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 high complexity as a router over thousands of sources, the description covers the necessary context: scope, use cases, comparisons, output mention ('structured answer with stable pipeworx:// citation URIs'), and alternatives. The absence of an output schema is partially compensated by the citation description, though a bit more detail on response shape would push it to 5.

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 parameter schema already explains the 'question' parameter and its aliases. The description adds value by defining what kinds of questions are appropriate (factual, real-world, authoritative data) and providing concrete examples like 'current US unemployment rate' and 'Apple's latest 10-K', which guides parameter formulation beyond the schema.

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 question-answering router: it 'routes the question to the right one of 5,953 tools across 1551 verified sources' and returns 'the structured answer with stable pipeworx:// citation URIs.' It explicitly differentiates itself from siblings like ask_pipeworx_grounded and deep_research, making its role unmistakable.

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 exceptionally explicit about when to use this tool: 'PREFER OVER WEB SEARCH', 'START HERE for most questions', and lists trigger phrases ('what is', 'look up', 'find', 'get the latest'). It also tells the agent when to step up to alternatives: ask_pipeworx_grounded for hallucination-resistant single answers and deep_research for broad/multi-part questions.

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