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

No annotations are provided, so the description carries the full burden of behavioral disclosure, but it only says 'with AI' and does not explain return format, supported languages, whether both detection and translation results are returned, or any latency/cost implications. There is no output schema to fill in these gaps.

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 compact and front-loads the core operations, but the 'AI Language:' prefix repeats the tool name and 'with AI' adds little meaning. It is appropriately short, yet not every word 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?

For a one-parameter tool with no output schema, the description is thin: an agent cannot tell whether the result is a language code, translated text, or both. The presence of dedicated sibling tools further increases selection ambiguity, so more context is needed.

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 single parameter 'content' is already 100% schema-documented, which sets the baseline at 3. The description implies the content is natural-language text to process, but it does not clarify how one content value drives both detection and translation or what format is expected.

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 explicitly names two operations, 'Language detection and translation,' and ties them to the AI-language context. It is clear about the general purpose, but it does not distinguish this combined tool from dedicated siblings like x402-language-detect, x402-language-guess, or x402-ai-translate.

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?

There is no guidance on when to use this tool instead of x402-language-detect, x402-language-guess, or x402-ai-translate. The description also does not state whether both operations happen in one call or whether a target language must be specified, leaving selection and invocation to inference.

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