Scenario.com MCP Server

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 states a read operation ('Get'), which implies it's likely safe and non-destructive, but doesn't confirm this or add any other behavioral traits. It lacks details on permissions, rate limits, error handling, or the format of the returned scores (e.g., numeric values, timestamps), which are crucial for a tool with unspecified output schema.

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—a single sentence that directly states the tool's purpose without any unnecessary words. It's front-loaded and efficient, making it easy to parse quickly, though this brevity contributes to gaps in other dimensions like guidelines and transparency.

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 complexity of a tool with 2 parameters (one undocumented), no annotations, and no output schema, the description is incomplete. It doesn't explain what 'prompt scores' entail (e.g., evaluation metrics, user ratings), how results are structured, or any behavioral constraints. For a data retrieval tool in a context-rich environment with many siblings, more detail is needed to ensure proper usage.

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 description mentions the 'modelId' parameter, aligning with the input schema's required parameter, but doesn't explain the optional 'prompt' parameter, leaving its purpose unclear. With schema description coverage at 50% (only 'modelId' has a description), the description adds minimal value beyond the schema—it clarifies that 'modelId' is for retrieving prompt scores, but fails to compensate for the undocumented 'prompt' parameter, resulting in a baseline score.

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 action ('Get') and the target resource ('prompt scores for the given modelId'), which is specific and understandable. However, it doesn't explicitly differentiate this tool from similar sibling tools like 'get-models-description-by-model-id' or 'get-models-examples-by-model-id', which also retrieve model-specific data, leaving some ambiguity about what distinguishes prompt scores from other model attributes.

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 (e.g., whether the model must exist or be accessible), exclusions, or how it differs from other 'get-models-*' tools in the sibling list, such as 'get-models-scores-training-dataset-by-model-id'. This lack of context makes it harder for an AI agent to choose appropriately among similar tools.

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