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create_chart

Generate visual charts from datasets by specifying visualization type, data source, and parameters for Apache Superset dashboards.

Instructions

Create a new chart.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slice_nameYesChart name
viz_typeYesVisualization type (e.g. 'bar', 'line', 'pie', 'table', 'big_number_total')
datasource_idYesID of the dataset to use
datasource_typeNo'table' for datasets (default)table
paramsNoJSON string of chart parameters/query context{}
descriptionNoOptional chart description
dashboardsNoList of dashboard IDs to add the chart to

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. 'Create a new chart' implies a write operation, but it doesn't disclose any behavioral traits such as required permissions, whether the chart is saved persistently, potential side effects (e.g., adding to dashboards), rate limits, or error conditions. This leaves significant gaps for an agent to understand how the tool behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with a single sentence 'Create a new chart.', which is front-loaded and wastes no words. While it may be under-specified, it earns full marks for brevity and clarity within its limited scope.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (7 parameters, write operation) and the presence of an output schema (which reduces the need to describe return values), the description is minimally adequate but incomplete. It lacks context about the chart's lifecycle, integration with dashboards, or error handling, making it insufficient for full understanding despite the structured data support.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 7 parameters thoroughly. The description adds no additional meaning beyond what the schema provides—it doesn't explain parameter relationships, default behaviors, or practical usage examples. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Create a new chart' clearly states the action (create) and resource (chart), but it's vague about what constitutes a chart in this context and doesn't distinguish it from sibling tools like 'create_dashboard' or 'create_dataset'. It provides basic purpose but lacks specificity about the chart's nature or scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. For example, it doesn't explain when to choose 'create_chart' over 'update_chart' or how it relates to 'create_dashboard' or 'create_dataset'. The description offers no context about prerequisites, dependencies, or typical use cases.

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

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