set_gradient_color

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

With no annotations, the description carries full responsibility and does well by explaining the core behavior: colors are driven by a measure, minColor/maxColor are endpoints, min/center/max set explicit stop values, and centerColor is optional for a 3-stop ramp. However, it does not disclose potential side effects like overwriting existing formatting or validation rules, which prevents a perfect score.

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?

Three well-structured sentences, front-loaded with the primary action and target. The second sentence explains the parameter logic, and the third notes the default. Every sentence adds distinct value without redundancy.

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 (12 params, no output schema, no annotations), the description covers the key non-obvious aspects: target visuals, exclusive use case, and parameter relationships. It does not mention return values or errors, but for a setter tool this is acceptable and the description is sufficient for correct invocation.

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 coverage is 67%, but the description adds significant relational meaning not present in the schema: it connects minColor/maxColor to the measure-driven fill, defines min/center/max as the stop values, and clarifies centerColor's optional role. This helps the agent correctly populate parameters beyond their individual descriptions.

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 ('Set a measure-driven GRADIENT-STOP saturation colour') and the exact resource (a card not targeted by set_color_scale, e.g., treemap/funnel/map dataPoint fill). It explicitly distinguishes this tool from the sibling set_color_scale, making the purpose unmistakable.

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 directly references the alternative tool set_color_scale and indicates that this tool is for cases that tool does not cover ('that set_color_scale does not target'), giving clear guidance on when to use it. It also specifies the default card value (dataPoint), helping with parameter decisions.

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