add_kpi_card

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

With no annotations, the description carries the full burden. It adds valuable behavioral context by stating the card is 'composed from proven primitives so it always renders', which is a meaningful reliability guarantee beyond the schema. It also describes the visual style, but does not disclose potential side effects (e.g., overwriting existing visuals), though the non-destructive nature seems intuitive.

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 compact and efficient, using two sentences to convey purpose, visual details, differentiation, and parameter guidance. It is front-loaded with the main action and contains no fluff, earning a high score.

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?

For a complex tool with 16 parameters, no annotations, and no output schema, the description covers the essentials: what it does, how to use key optional parameters, and how it differs from a sibling. It leaves color/position parameters to schema defaults, which is acceptable. Missing return-value description is mitigated by the absence of an output schema.

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 63%, so the baseline is 3. The description adds relational guidance for parameters: it links deltaMeasure to comparison and the trendMeasure + dateTable/dateColumn combination to sparkline. This clarifies how to configure the optional features, which is more than the schema's individual descriptions provide, elevating the 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 tool's purpose: 'Add a PREMIUM KPI card' with a detailed visual breakdown (white rounded panel, uppercase label, big value, optional delta and sparkline). It also distinguishes from a sibling tool by saying 'Far richer than add_card', making the specific resource and value proposition clear.

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 explicit usage context by comparing to add_card and explaining how to enable optional features ('Pass deltaMeasure for the comparison, and trendMeasure + dateTable/dateColumn for the sparkline'). It doesn't explicitly say when not to use alternatives like add_sparkline, but the premium positioning implies a clear choice for richer KPI visuals.

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