create_chart

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 details chart types and column usage but does not disclose behavioral traits like data size limits, performance, or error handling. It mentions 'default auto' for bins but lacks broader behavioral context.

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 concise, with a clear opening sentence and a structured list of basic chart types. It is front-loaded with the core purpose, though the list could be slightly more organized with bullet points for readability.

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 41 parameters and an output schema, the description covers the most common use cases (basic chart types) and references `get_resource_data()` for data input. It does not fully detail all 20+ chart types but is sufficient for typical 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?

With 56% schema description coverage, the description adds significant meaning beyond the schema. It groups chart types and maps columns (e.g., 'x_column', 'y_column') to specific chart behaviors, helping the agent select the right parameters for each chart type.

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 'Create interactive charts from data. Supports 20+ chart types.' and lists basic chart types with their column mappings. This distinguishes it from siblings like `create_animated_chart` or `create_scatter_3d`, providing a specific verb and resource.

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 clear context for basic chart types, explaining which columns to use for each type (e.g., 'line: x_column + y_column → time series, trends'). However, it does not explicitly state when not to use this tool versus sibling tools for specialized charts (e.g., 3D, animated).

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