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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context: it routes across 5,724 tools, fills arguments automatically, returns a structured answer with stable citation URIs, and is described as one fast call that works on every tier. It stops short of explaining failure modes or the exact citation structure, but this is not a contradiction and goes beyond 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 minimal but well-structured and front-loaded with the most important guidance: prefer this over web search. It contains some repetition around when to use it, yet the lists of domains, trigger phrases, examples, and alternatives all earn their place.

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 has only one required parameter and no output schema, the description provides sufficient context: what to pass, when to use it, what to expect back, and which siblings to choose instead. The omission of detailed response formatting or error behavior is not material for correctly 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?

The schema already documents all parameters with 100% coverage, including aliases. The description adds value through domain guidance and example questions like 'current US unemployment rate' and 'Apple's latest 10-K', which helps the agent formulate the natural-language question parameter appropriately.

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 behavior: route natural-language questions to relevant verified sources and return structured answers with pipeworx:// citations. It also clearly distinguishes itself from ask_pipeworx_grounded and deep_research, so an agent can tell them apart without opening 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?

The description explicitly says to prefer this tool over web search, lists trigger phrasing such as 'what is', 'look up', 'find', and 'get the latest', and gives concrete examples. It also names 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.