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create_dashboard

Create a new dashboard in Apache Superset to visualize data and monitor metrics. Define layout, add charts, and configure settings for data analysis.

Instructions

Create a new dashboard.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYes
slugNo
publishedNo
json_metadataNo
position_jsonNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Create a new dashboard' implies a write operation, but it doesn't disclose permissions needed, side effects, rate limits, or what the creation entails (e.g., whether it's immediately visible). This is a significant gap for a mutation tool with zero annotation coverage.

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 a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, making it easy to parse quickly. Every word earns its place, though it could benefit from more detail.

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 (5 parameters, 1 required, no annotations) and the presence of an output schema, the description is incomplete. It doesn't explain parameters or behavioral traits, but the output schema might cover return values. For a creation tool with multiple parameters, more context is needed to be fully helpful.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate by explaining parameters. It adds no meaning beyond the schema—it doesn't clarify what 'title', 'slug', 'published', 'json_metadata', or 'position_json' do, their formats, or examples. With 5 parameters and low coverage, this is inadequate.

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 dashboard' clearly states the action (create) and resource (dashboard), but it's vague about what a dashboard entails in this context and doesn't differentiate from sibling tools like 'create_chart' or 'create_dataset' beyond the resource name. It meets the basic requirement of stating what the tool does without being tautological.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, when not to use it, or how it relates to siblings like 'copy_dashboard', 'update_dashboard', or 'publish_dashboard'. The agent must infer usage from context alone.

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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