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plot_interactive_barchart

Creates interactive grouped bar charts from data files, aggregating numeric columns by categorical groups with optional color splitting.

Instructions

Generates an interactive Plotly grouped bar chart. x_column: categorical column for the x-axis groups. y_column: numeric column to aggregate. aggregation: how to aggregate y per group — 'mean' (default), 'sum', 'count', or 'median'. color_column: optional column to split bars by colour.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYes
x_columnYes
y_columnYes
aggregationNomean
color_columnNo
data_file_pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses that the chart is interactive and grouped, and explains parameters like aggregation. However, it does not mention the return type (plotly figure) or any side effects, leaving behavioral gaps.

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

Conciseness4/5

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

The description is concise with 5 sentences and no fluff. However, it misses necessary information about the two omitted parameters, which slightly detracts from efficiency.

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

Completeness2/5

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

Given the complexity (6 params, no annotations, an output schema exists but is not described), the description is incomplete. It fails to explain required parameters data_file_path and title, and does not describe the return value. Sibling tools are numerous, so more differentiation and completeness are needed.

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 explain all parameters. It covers x_column, y_column, aggregation, and color_column well, but completely omits data_file_path and title, which are required and critical. This incomplete coverage leaves the agent uncertain about two key inputs.

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

Purpose5/5

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

The description clearly states it generates an interactive Plotly grouped bar chart. The verb 'Generates' and resource 'grouped bar chart' are specific, and the tool is distinct from siblings like plot_static_barchart or plot_interactive_boxplot.

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

Usage Guidelines3/5

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

The description implicitly provides usage context by specifying that x_column is categorical and y_column is numeric, but it does not explicitly advise when to use this tool over alternatives like plot_static_barchart or other interactive plots. No comparative guidance or exclusions are given.

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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