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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safe read-only nature is fully covered by structured data. The description adds no additional behavioral context such as authentication or rate limits, but none is needed here; it provides conceptual rather than behavioral transparency.

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?

Two sentences, each earning its place: the first defines the tool's content and structure, the second gives a precise invocation directive. The description is information-dense with no filler or repetition.

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 an introductory, zero-parameter, read-only explanatory tool, the description is complete. It tells the agent exactly what will be learned, how datasets relate, and when to call it first, without needing to document parameters or return formats.

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?

The tool has zero parameters and the input schema is empty with 100% schema description coverage, so no parameter documentation is required. The description correctly avoids inventing parameter details, and the baseline for a zero-parameter tool is satisfied.

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 ('Explain') and resource ('the manufacturer's data model'), and details the content: what each query dataset means and how they relate. The part -> specification -> requisition -> order chain with production and pricing distinguishes this from sibling tools like describeQueryableFields and describeConfiguration.

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 instruction 'Call this first to understand how to traverse between datasets' gives explicit usage context and temporal placement among sibling tools. It does not name alternatives or exclusions, but the 'first' guidance is strong enough for an agent to know when to use it.

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