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$ 𝚗𝚙𝚡 𝚌𝚑𝚊𝚛𝚝𝚕𝚒 

Or global install it.
$ npm i -g chartli

# Skill for your agents
$ npx skills add ahmadawais/chartli 

If you work in terminals and want quick data visualization without leaving your workflow, try it.

⌘ let's go!!

SVG mode has 2 render paths: circles (scatter plot) and lines (polylines). Output is valid XML you can pipe straight to a file or into another tool.


Zero config by default, every dimension overridable (-w width, -h height, -m SVG mode). 

No config files. 
No themes. 
No dashboards.

The bars renderer uses 4 shading levels (░▒▓█) to visually separate series without color. Works on any terminal, any font.

Heatmap maps values to a 5-step intensity scale across a row×column grid, so you can spot patterns in tabular data at a glance.

The braille renderer is my fav. Each braille character encodes a 2×4 dot grid, so a 16-wide chart gives you 32 pixels of horizontal resolution. Free anti-aliasing from Unicode.

0.0 0.1 0.1 0.1
0.2 0.4 0.2 0.4
0.3 0.2 0.4 0.2

Composes with pipes:

$ cat metrics.txt | chartli -t spark

S1 ▁▂▃▄▅▆
S2 ▁▄▂▇▅█
S3 ▁▂▄▃▆▅
S4 ▁▄▂▇▂▇

- heatmap (2D grid, ░▒▓█ intensity mapping)
- unicode (grouped bars with ▁▂▃▄▅▆▇█ sub-cell resolution)
- braille (⠁⠂⠃ 2×4 dot matrix, highest density)
- svg (vector output, circles or polylines)

Input format is dead simple: rows of space-separated numbers. Multiple columns = multiple series.

$ npx chartli data.txt -t ascii -w 24 -h 8

8 chart types spanning a fun range of Unicode density:

- ascii (line charts with ○◇◆● markers)
- spark (▁▂▃▄▅▆▇█ sparklines, one row per series)
- bars (horizontal, ░▒▓█ shading per series)
- columns (vertical grouped bars)

Introducing chartli 📊

A CLI for rendering charts in your terminal from numeric text data.

$ 𝚗𝚙𝚡 𝚌𝚑𝚊𝚛𝚝𝚕𝚒 

I wanted terminal charts with zero setup. No browser, no Python env, no matplotlib. Pipe numbers in, get a chart out.

Again built it my coding taste using Command Code.

We're working on it right now!

🍐🍐🍐🍐

Build on top of Elicit. Now you can build research dashboards or combine Elicit evidence with your own datasets.

Integrate Elicit into your workflow. Call the API from Claude or ChatGPT to get real citations while writing a paper, or build a Slack bot that pulls evidence into team discussions. We built one internally to settle debates with data instead of anecdotes.