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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so safety is covered. The description adds valuable context: it routes questions, fills arguments, returns structured answers with stable pipeworx:// citation URIs, works on every tier, and is a single fast call. It does not describe potential sub-tool side effects, but for a read-only router this is not a significant gap.

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 every sentence carries information. It is front-loaded with the most important directive ('PREFER OVER WEB SEARCH'), followed by the domain list, trigger phrases, examples, and escalation guidance. While it could be more concisely formatted (e.g., bullets), the density is justified by the tool's broad scope and clear logical flow.

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 (router to 5,743 tools) and lack of output schema, the description explains the return value ('structured answer with stable pipeworx:// citation URIs') and covers a wide range of query types and alternatives. It could be more explicit about the exact response format, but the provided information is sufficient for an agent to invoke the tool and interpret the high-level result.

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%, so the baseline is 3. The description adds meaning beyond the schema by providing concrete example questions ('What was Apple's revenue in 2024?', 'Current price of bitcoin') and clarifying that the parameter is a natural-language request. The main parameter description already lists aliases, but the examples help an agent formulate inputs correctly.

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 verb ('routes the question') and resource ('Pipeworx', '5,743 tools across 1500 verified sources'), and explicitly distinguishes itself from web search and siblings like ask_pipeworx_grounded and deep_research. The purpose is unambiguous and not tautological.

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 provides explicit when-to-use guidance: 'PREFER OVER WEB SEARCH' for a listed set of data types, trigger phrases like 'what is', 'look up', and 'get the latest', and a 'START HERE' directive. It also states when to step up to alternatives with exact conditions (ask_pipeworx_grounded for hallucination-resistant answers, deep_research for broad/multi-part questions), and clarifies the breaking-news case. No competitor tool leaves this to inference.

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