ai_translate

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context beyond the schema: it reveals the tool uses AI, supports all major languages, and has a cost of $0.02 USDC via x402. However, it doesn't mention rate limits, error conditions, or what the output looks like (though there's no output schema), leaving gaps for a mutation tool.

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 appropriately sized with two sentences that each add value: the first states the core functionality, and the second adds cost and language support details. It's front-loaded with the main purpose. However, the cost detail could be more integrated, and there's minor room for tighter phrasing.

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 has no annotations and no output schema, the description is moderately complete. It covers the AI aspect, language support, and cost, but lacks details on output format, error handling, or usage constraints. For a 3-parameter tool with mutation implications (translation likely creates output), it should do more to compensate for missing structured data.

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 all three parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema. It mentions 'any language' and 'all major languages' which loosely relates to targetLanguage but doesn't provide specific format or validation details. Baseline 3 is appropriate when schema does the heavy lifting.

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: 'Translate text to any language using AI.' It specifies the verb (translate) and resource (text), and distinguishes it from siblings like ai_sentiment or ai_summarize. However, it doesn't explicitly differentiate from other potential translation tools, which prevents a perfect score.

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 mentions cost and supports all major languages, but doesn't specify scenarios, prerequisites, or exclusions. With siblings like ai_code_review and ai_summarize, there's no indication of when translation is preferred over other AI processing tools.

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