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. It mentions 'trigger a restyle process' but lacks details on behavioral traits such as whether it's a read-only or mutating operation, expected runtime, rate limits, authentication needs, or what the output entails (e.g., returns an image, job ID, or error). This is inadequate for a tool with 13 parameters and no 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 a single, efficient sentence that front-loads the core action and inputs without unnecessary words. It earns its place by clearly stating the tool's purpose in a compact form, making it easy to parse quickly.

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 (13 parameters, no annotations, no output schema), the description is insufficient. It lacks information on output behavior, error handling, or operational constraints, which are critical for an AI agent to invoke it correctly. The high parameter count and absence of structured behavioral data require more descriptive context than provided.

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 high at 85%, so the schema already documents most parameters well. The description adds minimal value by hinting at the inputs ('sketch image (or other image)' and 'reference style images'), which loosely maps to 'image' and 'styleImages' parameters, but doesn't provide additional context beyond the schema's descriptions. Baseline 3 is appropriate given the schema's thoroughness.

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 ('trigger a restyle process') and specifies the inputs ('from one sketch image (or other image) and one or more reference style images'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'post-controlnet-inferences' or 'post-img2img-inferences' that might also involve image transformation, leaving some ambiguity about its unique role.

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. With many sibling tools for image processing (e.g., 'post-controlnet-inferences', 'post-img2img-inferences'), there is no indication of specific scenarios, prerequisites, or exclusions for this restyle tool, leaving the agent to infer usage from context alone.

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