A specialized data visualization skill for creating and analyzing stacked composition charts to reveal structural trends.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install parfait-charts
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install parfait-charts using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Parfait Charts?
Parfait Charts is a powerful visualization framework designed for high-density composition analysis. This skill enables AI agents to generate structured, layered bar charts that represent how different segments—such as revenue streams, cost centers, or portfolio assets—contribute to a whole over specific time periods.
By leveraging this tool within Openclaw Skills, users can transform raw numerical data into intuitive visual narratives. It excels at highlighting the "parfait" effect: showing the distinct layers of a business or project and how their relative proportions shift, providing immediate clarity on growth drivers and structural changes.
Parfait Charts Use Cases
- Revenue Mix Analysis: Visualize how different product lines or services contribute to total company income.
- Cost Structure Breakdown: Analyze fixed and variable cost components to identify efficiency opportunities over time.
- Portfolio Management: Display segment breakdowns for investment portfolios to monitor diversification and risk exposure.
- Market Share Tracking: Compare the performance of various business units against the total market size.
How Parfait Charts Works
- Data Intake: The skill receives raw data or arguments regarding a specific subject like revenue, costs, or segments.
- Structural Mapping: It organizes the data into a period-based matrix (e.g., Year-over-Year) with defined segments.
- Visualization Generation: It renders a stacked representation to show both individual segment performance and total aggregate values.
- Trend Calculation: The skill automatically calculates share percentages and growth rates for each layer.
- Insight Extraction: It synthesizes the visual data into strategic implications and key performance observations.
Parfait Charts Setup
To integrate this functionality into your environment, add the skill to your agent configuration. You can initialize the environment using the following commands:
# Install the Openclaw Skills CLI if not already present
npm install -g @openclaw/cli
# Add the parfait-charts skill to your local repository
openclaw add parfait-charts
Parfait Charts Data Schema & Taxonomy
The skill organizes data using a period-centric taxonomy to ensure consistent trend mapping. It typically outputs a structured table followed by qualitative analysis.
| Attribute | Description |
|---|---|
| Period | The time dimension (e.g., Year, Quarter, Month) |
| Segments | 3-5 distinct categories represented as chart layers |
| Total | The aggregate sum of all segments per period |
| Share % | The relative percentage of each segment vs. the total |
| Growth | The numerical and percentage change over the time series |
Parfait Charts Advanced Features
- Automated Mix-Shift Detection: Identifies when a sub-segment is outperforming the aggregate and suggests strategic pivots.
- Percentage Scaling: Automatically converts absolute values into relative composition views for better comparison.
- Strategic Implication Engine: Generates high-level business recommendations based on the delta between periods.
- Multi-Agent Compatibility: Seamlessly shares chart data across different Openclaw Skills for comprehensive reporting.
SKILL.md
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