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apply_chart_theme

Apply a visual theme (dark, light, or infographic) to a Plotly chart figure, and optionally add callout annotations or shaded highlight zones.

Instructions

Apply visual theme to a chart figure from create_chart().

Themes: 'dark' (data-journalism), 'light' (clean), 'infographic' (large type). Add annotations: [{"text": "...", "x": val, "y": val}] for callouts. Add zones: [{"x_start": val, "x_end": val, "label": "..."}] for highlights.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
themeNo'dark', 'light', or 'infographic'dark
figureYesPlotly figure dict from create_chart()
annotationsNoCallout annotations
highlight_zonesNoShaded highlight regions

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses theme options and optional features but lacks details on side effects (e.g., overwriting existing theme) or error handling for invalid figures.

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?

Three sentences, front-loaded core purpose, followed by theme options and optional features. No wasted words, but could be slightly more structured.

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 output schema exists, return values need not be explained. However, missing details on preconditions (figure must be from create_chart) and whether the tool modifies in place or returns a new figure.

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

Parameters4/5

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

With 100% schema coverage, the description adds value by explaining themes with examples and showing structure for annotations and zones, going beyond the schema's descriptions.

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 the tool applies a visual theme to a chart figure from create_chart(), lists three themes, and distinguishes itself from sibling tools like add_chart_annotation by offering bulk application.

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

Usage Guidelines4/5

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

The description implies usage after creating a chart, and mentions optional annotations and zones, but does not explicitly state when not to use it or provide alternatives for individual modifications.

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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