Are the charts compatible with Markdown files?

Absolutely. Because the charts are generated as plain text ASCII, they can be wrapped in code blocks in any Markdown file, PR description, or documentation site.

How does it handle large datasets with hundreds of values?

The skill includes an automated compression strategy using sampling or bucketing to ensure the chart remains readable within a standard terminal width (defaulting to 60 columns).

Can I use Unicode characters for higher resolution visuals?

Yes, the skill supports optional Unicode blocks for smoother visual representation, but it always includes an ASCII-only fallback to ensure compatibility across all terminal environments.

Does this skill perform statistical analysis or inference?

No, this skill is specifically designed for visualization. It plots the data provided but does not perform statistical inference, forecasting, or outlier detection.

ASCII Mini Charts

Name: ASCII Mini Charts
Author: partme-ai

bypartme-ai

•

분석 및 모니터링

Generates lightweight ASCII-based sparklines, bar charts, and line graphs for immediate trend inspection within terminal environments.

ASCII Mini Charts provides a streamlined way to visualize numerical data trends directly in your terminal or documentation without external dependencies or heavy GUI tools. It allows developers and data analysts to quickly generate annotated sparklines and simple graphs that are copy-paste friendly and optimized for plain-text environments like Git commits, logs, and Markdown files. By supporting linear and logarithmic normalization and offering compression strategies for long data series, it transforms raw numeric lists into insightful visual summaries while maintaining a compact, terminal-friendly layout.

주요 기능

01Automatic data normalization with support for linear and logarithmic scales

02Plain-text ASCII output for easy copy-pasting into logs and documentation

03Multiple chart types including sparklines, bar charts, and line graphs

0490 GitHub stars

05Built-in compression and sampling strategies for handling large datasets

06Smart annotations for highlighting minimum, maximum, and current values

사용 사례

01Visualizing server performance metrics directly in log files or CI/CD outputs

02Adding lightweight visual reports to Markdown documentation and PR comments

03Quickly inspecting data trends during local development without opening a browser

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add partme-ai/full-stack-skills ascii-mini-charts

For use in Claude.ai and ChatGPT

Download Skill