get_languages

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns language data (names, codes, etc.), which is useful behavioral context. However, it lacks details on permissions, rate limits, error handling, or whether it's a read-only operation (implied but not stated). The description adds some value but leaves gaps in behavioral traits.

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 concise and well-structured: two sentences that front-load the purpose and detail the return values. Every sentence earns its place by providing essential information without redundancy. It efficiently communicates the tool's function and output.

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?

Given the tool's low complexity (0 parameters) and the presence of an output schema, the description is reasonably complete. It explains what the tool does and what it returns, which is sufficient for the agent. However, it could improve by addressing usage context or behavioral aspects like permissions, but the output schema likely covers return values, reducing the burden.

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 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to add parameter semantics, so it appropriately focuses on output. A baseline of 4 is justified as it compensates for the lack of parameters by detailing the return data, which is helpful for the agent.

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: 'Get all languages configured for the Nativ workspace.' It specifies the verb ('Get') and resource ('languages'), and distinguishes it from siblings like 'translate' or 'get_style_guides' by focusing on workspace language configurations. However, it doesn't explicitly differentiate from all siblings (e.g., 'get_brand_voice' might also retrieve configurations).

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for usage, or comparisons to sibling tools like 'get_style_guides' or 'get_brand_voice'. The agent must infer usage based on the purpose alone, which is insufficient for optimal tool selection.

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