superset_chart_create

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

With no annotations provided, the description carries the full transparency burden, and it excels: it discloses the 'not registered' error for deprecated viz types, warns that moment.js date formats render as literal text, explains that big_number_total fonts can cause scrolling, and notes that country_map tooltips are clipped unless CSS is applied. It also clarifies that query_context is required for chart_get_data to work, which is a non-obvious behavior.

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 very long, but well-structured into clearly labeled sections (Args, IMPORTANT, CRITICAL, REFERENCE parameters, etc.) and front-loaded with the core purpose. It could be trimmed—CSS recommendations and the exact deprecation list are arguably extra—but the density of actionable information is high and the structure keeps it scannable, so it earns a high but not perfect 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?

Despite the tool's complexity and lack of annotations, the description covers all seven parameters, includes error-prone edge cases, provides exact format examples, and explains prerequisites like datasource_id and query_context. Since an output schema exists, not detailing return values is acceptable, and the description is otherwise comprehensive enough 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?

The input schema has 0% description coverage, so the description must fully compensate, and it does. It explains viz_type with a complete list of valid values and deprecated aliases, datasource_id origin, datasource_type default, params as a JSON string with detailed formatting requirements, query_context's role, and dashboards as a list of IDs. This adds immense meaning beyond the bare schema names.

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 opens with the specific verb-object statement 'Create a new chart,' which precisely identifies the action and resource. It also enumerates the chart types and parameters, making it clear this is the creation tool and not an update, delete, or copy operation among the chart-related sibling tools.

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 gives clear usage context: it lists required arguments, tells the agent to pull datasource_id from superset_dataset_list, and warns against deprecated viz_type values that will error. It does not explicitly mention alternatives like superset_chart_update for modifications or superset_chart_get for reads, so it falls short of full when/when-not coverage, but the creation-specific guidance is clear.

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