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

Annotations already declare this is read-only, idempotent, and non-destructive, so the description does not need to repeat that. It adds meaningful behavioral context beyond annotations: the tool routes to internal tools, fills arguments, returns structured answers with citation URIs, works on every tier, and makes one fast call. It could additionally describe failure or ambiguity behavior, but the existing context is strong.

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 well-structured: it opens with the most important instruction (prefer over web search), states the mechanism, gives trigger phrases and examples, and then routes to alternatives. The example list is extensive but useful. It could be slightly tightened, but it is not redundant or wasteful.

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 that there is no output schema, the description compensates by describing the return format (structured answer with stable pipeworx:// citation URIs). It covers the tool's scope, trigger phrases, examples, tier availability, speed, and related alternatives. An agent has enough context to decide when to call this tool and what to expect from it.

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 input schema has 100% coverage: the `question` parameter is described as natural language and all aliases are explicitly named. The description adds usage examples and a trigger phrase list, but it does not add new meaning about the parameter beyond what the schema already provides. Baseline 3 applies because the schema does the heavy lifting.

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 the tool's function: it routes factual questions to one of 5,718 tools across 1,496 verified sources and returns structured answers with stable citation URIs. It is explicitly differentiated from siblings like ask_pipeworx_grounded and deep_research, so an agent can immediately tell what this tool does and where it fits.

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 names concrete step-up alternatives: ask_pipeworx_grounded for hallucination-resistant single answers and deep_research for broad/multi-part questions, leaving no ambiguity about routing.

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