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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds meaningful behavioral context beyond annotations: it fills arguments automatically, returns structured answers with stable pipeworx:// citation URIs, makes one fast call, and works on every tier. It could also mention failure modes or citation behavior details, but it does not contradict annotations and enriches the behavioral picture.

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 information-dense and well-structured: it opens with the core directive, then scope, examples, default behavior, and escalation path. Every section earns its place, though some promotional phrasing could be trimmed; the length is justified by the tool's broad role.

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?

Even without an output schema, the description explains the return format ('structured answer with stable pipeworx:// citation URIs'), covers the trigger conditions, provides examples, and names the relevant sibling alternatives. For a one-required-parameter tool, this is complete enough for an agent to select and invoke 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 coverage is 100% with the 'question' parameter and aliases clearly described, so the baseline is 3. The description goes beyond this by providing a wide range of example questions ('current US unemployment rate', 'Apple's latest 10-K', etc.) and listing query domains, which helps an agent understand what kind of input the tool expects.

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 states a specific verb ('routes', 'fills arguments', 'returns') and resource ('5,743 tools across 1500 verified sources') and clearly positions this as the default factual-question answering entry point. It differentiates from siblings by naming ask_pipeworx_grounded and deep_research and describing their distinct roles, 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?

Usage is explicit: 'PREFER OVER WEB SEARCH', 'START HERE for most questions', and it lists concrete trigger phrases ('what is', 'look up', 'find', etc.) plus domain examples. It also gives clear escalation rules: use ask_pipeworx_grounded for hallucination-resistant single answers and deep_research for broad/multi-part questions, and explains the breaking-news case.

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