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ceeyang-ai

Viz MCP Server

by ceeyang-ai

create_line_chart

Generate a line chart from numeric x and y data points with customizable title, axis labels, color palette, and point markers. Output as SVG or PNG.

Instructions

Create a line chart.

Args: x_values: X-axis data points y_values: Y-axis data points title: Chart title xlabel: X-axis label ylabel: Y-axis label palette: Color palette: default, vibrant, pastel, monochrome show_points: Show data point markers output: 'svg' for inline SVG, 'png' for file path

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
x_valuesYes
y_valuesYes
titleNoLine Chart
xlabelNo
ylabelNo
paletteNodefault
show_pointsNo
outputNosvg

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description must cover behavioral traits. It mentions output format options (svg/png) and lists parameters with defaults, which adds some transparency. However, it does not disclose side effects, authentication requirements, or error handling behavior.

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 concise and well-structured: a clear purpose statement followed by a compact list of parameters. Every sentence is informative, and the information is front-loaded.

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

Completeness4/5

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

Given the tool's moderate complexity (8 parameters, output options), the description covers key aspects: purpose, parameters, and output format. The presence of an output schema reduces the need to document return values. Minor gaps include lack of error conditions or performance notes.

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?

The description provides semantic explanations for all 8 parameters (e.g., 'X-axis data points', 'Color palette: default, vibrant, pastel, monochrome'), which adds value beyond the schema's titles and types. With 0% schema description coverage, the description compensates adequately, though details are somewhat brief.

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 starts with 'Create a line chart', which is a specific verb+resource that clearly indicates the tool's function. It distinguishes itself from sibling tools like create_bar_chart or create_scatter_plot by specifying 'line chart'.

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 (e.g., bar chart, scatter plot). The description simply states what it does without context on appropriate use cases or when to avoid it.

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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