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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is established. The description adds valuable behavioral context: it returns a copy-pasteable example and notes the output is the 'exact request shape,' which helps an agent know what to expect. It does not contradict annotations and adds relevant information beyond the structured hints.

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 two sentences with no redundancy. The first sentence states the primary function and lists the clients; the second provides the usage context. It is front-loaded with the core purpose and every sentence 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?

The tool is simple with only 2 parameters and an output schema exists, so the description does not need to explain return values. The description covers what the tool does, when to use it, and the client options. There are no missing elements that would prevent an agent from calling 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?

The input schema covers 100% of parameters with clear descriptions (client enum and multi_label boolean). The description does not add additional parameter semantics beyond what the schema provides; it only mentions 'given client' without extra detail. Since schema coverage is high, the baseline of 3 is appropriate.

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 the tool's purpose: returning a copy-pasteable example for specific clients (curl, javascript, python, cli, mcp). It uses a specific verb ('return') and names the resource (classifier.dev) and the exact set of clients. It also distinguishes itself from sibling doc tools by focusing on request shapes rather than documentation.

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 explicitly states when to use the tool: 'Use this when you are about to write integration code and want the exact request shape rather than reading the whole reference.' This provides a clear condition and contrasts with an alternative (reading the whole reference), which is likely covered by sibling tools like read_doc.

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