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

Annotations already mark the operation read-only and idempotent; the description adds that an API key is required, outputs are base64-encoded, invalid models return diagnostics, and include_docs incurs a slower execution. This goes beyond the structured annotations without contradicting them.

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?

Three sentences with the core purpose front-loaded. Each sentence covers a distinct aspect: action, prerequisites/returns, and optional behavior, with no wasted words.

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 a two-parameter tool with rich annotations and no output schema, the description is sufficient: it names required auth, return format, error behavior, and the optional flag. An agent has enough information to 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 description coverage is 100%, so the schema already documents both parameters fully. The description mentions 'from a YAML model' and optionally re-states include_docs=true, but it does not add new meaning beyond what the input schema provides.

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 and resource: it generates OPC UA NodeSet2.xml and Symbols.CSV from a YAML model. This clearly distinguishes it from sibling tools like validate or reverse by naming both the input and the output artifacts.

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 phrase 'from a YAML model' and the output artifacts establish a clear use case: producing NodeSet2 artifacts from a YAML source. It does not explicitly name alternatives or provide when-not-to-use conditions, but the context is clear and it includes an important prerequisite (API key).

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