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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds valuable behavioral context: it routes to one of 5,908 tools, fills arguments, and returns structured answers with stable pipeworx:// citation URIs. This goes beyond the annotations and helps the agent anticipate the tool's routing behavior, though it does not mention auth, rate limits, or failure modes.

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 front-loaded with the most important directive ('PREFER OVER WEB SEARCH') and then lists concrete use cases and examples, which is effective. It is somewhat long and repeats 'even if web search could also answer it' twice, but the length is justified by the tool's broad domain and routing behavior.

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 complexity and the absence of an output schema, the description covers the essential context well: what types of questions to ask, example queries, routing behavior, and the citation return format. It could be more complete by describing edge cases or limitations, but for a general factual-question router it provides enough for an agent to call 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%: all six parameters are documented as aliases for the natural-language question. The description itself adds little parameter-specific meaning beyond reinforcing that the input is a factual question. Per the baseline for high schema coverage, a score of 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 the tool's action: it acts as a router that answers factual questions using Pipeworx's verified tools and returns structured answers with citations. It is specific about the resource and scope (current and historical data, authoritative sources). However, it does not differentiate itself from sibling tools like ask_pipeworx_beta or ask_pipeworx_grounded, which lowers the score from 5.

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 strong explicit usage guidance: 'PREFER OVER WEB SEARCH' and 'START HERE for most questions,' with concrete examples of triggering phrases and sample questions. It clearly establishes when to use this tool over general web search, but it does not explicitly explain when to choose this tool over its sibling ask_pipeworx variants or deep_research, so it lacks full when-not/alternatives coverage.

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