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

Annotations already cover read-only, idempotent, open-world, non-destructive behavior. The description adds meaningful behavioral context: it routes to thousands of tools, fills arguments, returns structured answers with citation URIs, and claims 'one fast call' and 'works on every tier.' This goes beyond the annotation set, though it doesn't detail potential latency variation 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 dense yet organized: preference statement, functional summary, query trigger phrases, examples, default-entry guidance, and alternative routing are all present without repetition. Each sentence carries weight, and the most critical decision guidance ('PREFER OVER WEB SEARCH') is front-loaded.

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?

Despite having no output schema, the description explains the return value ('structured answer with stable pipeworx:// citation URIs') and the breadth of coverage. It also addresses edge cases like breaking news and provides examples spanning finance, health, patents, weather, and crypto. Given the tool's complexity, this is a complete picture for selection and invocation.

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%, with each parameter labeled as an alias for 'question,' so the baseline is 3. The description adds a few illustrative queries ('current US unemployment rate', 'Apple's latest 10-K') that clarify acceptable input semantics, but it doesn't materially expand on the schema's already-clear natural-language parameter definition.

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 opens with 'PREFER OVER WEB SEARCH' and states the tool's core action: routes questions to one of 5,743 tools across 1,500 verified sources and returns structured answers with stable pipeworx:// citation URIs. It is sharply distinguished from siblings by naming ask_pipeworx_grounded and deep_research as alternatives, leaving no doubt about which tool to use.

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?

Provides explicit when-to-use guidance: 'Use whenever the user asks...' with concrete phrases and examples, then states 'START HERE for most questions.' It names exact conditions for stepping up to ask_pipeworx_grounded (hallucination-resistant single answer with verbatim evidence + confidence) and deep_research (broad/multi-part fan-out), as well as a breaking-news caveat.

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