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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds meaningful behavioral context: it routes questions internally, fills arguments, returns structured answers with stable pipeworx:// citation URIs, and handles live news via feeds. It does not mention rate limits or failure modes, but the annotation coverage lowers the burden and the added detail is genuinely useful.

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 dense and front-loaded with the most important directive ('PREFER OVER WEB SEARCH'). It covers scope, examples, routing guidance, and sibling escalation. There is minor redundancy (the preference over web search is repeated in the opening and near the end), so it is not maximally concise, but every section earns its 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?

For a complex routing tool with no output schema, the description covers all key aspects: what it does, what kinds of questions to use it for, what it returns (structured answer with citation URIs), when to choose alternatives, and illustrative examples. An agent has enough information to invoke it correctly and set expectations about the response.

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%, so the baseline is 3. The description does not add parameter-level syntax but embeds multiple natural-language examples ('current US unemployment rate', 'Apple's latest 10-K', 'active clinical trials for GLP-1') that clarify the expected format of the question parameter, which exceeds the baseline.

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 a specific purpose: answering factual questions about real-world entities by routing them to one of 5,743 tools across 1,500 verified sources and returning structured answers with citation URIs. It explicitly distinguishes itself from web search and from siblings like ask_pipeworx_grounded and deep_research, so an agent can tell them apart.

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 signals ('Use whenever the user asks what is...') and names concrete alternatives with trigger conditions ('Step up only when needed: for a hallucination-resistant single answer... use ask_pipeworx_grounded; for a broad/multi-part question... use deep_research'). It also declares itself the default entry point ('START HERE'), which fully resolves the routing decision.

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