Scenario.com MCP Server

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. The description only states the basic function without mentioning critical behaviors: it doesn't indicate if this is a read-only or mutating operation, what permissions are required, rate limits, error handling, or output format. For a tool with 7 parameters including AI-related settings like temperature and seed, this lack of behavioral context is a significant gap.

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 extremely concise at one sentence with no wasted words. It's front-loaded with the core purpose. While it may be too brief for completeness, it earns full points for conciseness as every word contributes directly to stating the tool's function without redundancy or fluff.

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 complexity (7 parameters including AI generation settings), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, how errors are handled, or the relationship between translation and parameters like 'images' or 'seed'. For an inference tool with multiple configuration options, more context about behavior and results is needed to be adequately complete.

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 71% (5 of 7 parameters have descriptions), so the schema does substantial work. The description adds no parameter-specific information beyond implying the 'prompt' parameter contains text to translate. It doesn't explain how parameters like 'images', 'dryRun', or 'ensureIPCleared' relate to translation, nor does it provide usage examples or constraints. With high schema coverage, the baseline is 3, but the description adds minimal value.

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 the tool's purpose as translating text to English, which is clear but vague. It specifies the verb 'translate' and target language 'English', but doesn't mention what type of translation this is (e.g., AI-based, batch, real-time) or distinguish it from sibling tools like 'post-caption-inferences' or 'post-describe-style-inferences' that might involve language processing. The description is functional but lacks specificity about the translation mechanism or scope.

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, limitations, or compare it to other translation-related tools in the sibling list (e.g., 'post-prompt-inferences' might handle text generation). There's no indication of when this tool is appropriate or when other tools should be used instead, leaving usage decisions entirely to inference.

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