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xueyetianya

Data Visualizer

by bytesagain4 · GitHub ↗ · v3.0.1 · MIT-0
cross-platform ⚠ suspicious
1058
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0
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15
Active Installs
21
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Install in OpenClaw
/install data-visualizer
Description
Terminal ASCII chart toolkit. Create bar charts, sparklines, histograms, and gauges from CSV or JSON data in the terminal.
README (SKILL.md)

data-visualizer

Terminal data visualization toolkit — create ASCII bar charts, sparklines, histograms, heatmaps, gauges, treemaps from data. Process CSV/JSON files with stats summaries, correlations, normalization, and pivoting. Export to SVG and HTML.

Commands

bar

Draw a horizontal bar chart from label:value pairs.

scripts/script.sh bar "Sales:42" "Revenue:87" "Profit:31"

histogram

Show frequency distribution of numeric values as a histogram.

scripts/script.sh histogram 10 15 20 20 25 30 30 30 35 40

sparkline

Render an inline sparkline chart from a series of values.

scripts/script.sh sparkline 4 8 15 16 23 42 38 29 18 10

heatmap

Display a color-coded heat grid from row/column data.

scripts/script.sh heatmap 3 4 1 5 9 2 8 3 7 4 6 1

treemap

Show proportional blocks for part-to-whole comparisons.

scripts/script.sh treemap "Chrome:65" "Safari:18" "Firefox:10" "Edge:7"

gauge

Display a gauge meter showing a value against a maximum.

scripts/script.sh gauge 73 100 "CPU Usage"

matrix

Render a CSV file as a formatted matrix/table view.

scripts/script.sh matrix data.csv

summarize

Compute min/max/average/median statistics for each numeric column in a CSV file.

scripts/script.sh summarize sales.csv

distribution

Show the value distribution of numeric data in a CSV file across bins.

scripts/script.sh distribution scores.csv 8

correlate

Compute a Pearson correlation matrix across all numeric columns in a CSV file.

scripts/script.sh correlate metrics.csv

normalize

Normalize all numeric columns to 0-1 range and output as CSV.

scripts/script.sh normalize raw_data.csv > normalized.csv

pivot

Group rows by a column and aggregate numeric values (sum, avg, min, max).

scripts/script.sh pivot sales.csv region

from-csv

Auto-visualize a CSV file with summary statistics.

scripts/script.sh from-csv data.csv

from-json

Auto-visualize a JSON file — shows structure, keys, and numeric column summaries.

scripts/script.sh from-json data.json

to-svg

Export CSV data as an SVG bar chart.

scripts/script.sh to-svg sales.csv

to-html

Export CSV data as an HTML table with styling.

scripts/script.sh to-html report.csv

help

scripts/script.sh help

version

scripts/script.sh version

Examples

# Quick terminal charts
scripts/script.sh bar "Q1:120" "Q2:185" "Q3:210" "Q4:170"
scripts/script.sh sparkline 10 20 30 25 40 35 50 45
scripts/script.sh gauge 78 100 "Memory"

# CSV analysis pipeline
scripts/script.sh summarize data.csv
scripts/script.sh correlate data.csv
scripts/script.sh pivot data.csv category

# Export
scripts/script.sh to-svg data.csv
scripts/script.sh to-html data.csv

Configuration

Variable Required Description
DATAVIZ_DIR No Data directory (default: ~/.local/share/data-visualizer/)

Data Storage

History logged in ~/.local/share/data-visualizer/history.log.

Requirements

  • bash 4.0+
  • python3 (for CSV processing, correlations, JSON parsing, SVG export)

Powered by BytesAgain | bytesagain.com | [email protected]

Usage Guidance
This skill appears to do what it claims: local CSV/JSON analysis and ASCII/SVG/HTML exports. Before installing or running it, review the bundled scripts (scripts/script.sh) yourself, ensure you have bash 4+ and python3, and be aware it will create ~/.local/share/data-visualizer/ and a history.log there. If you are cautious, run the script in a sandbox/container or review the full script for any unexpected commands. Note: the script contains some coding issues (shell arithmetic and heredoc variable-expansion mistakes) that may cause runtime errors — these are quality bugs, not indicators of deliberate malicious behavior.
Capability Analysis
Type: OpenClaw Skill Name: data-visualizer Version: 3.0.1 The data-visualizer skill contains a critical shell injection vulnerability in the `cmd_to_html` function within `scripts/script.sh`. This occurs because the script processes CSV lines using `echo "$line"` inside a subshell expansion, which allows for arbitrary command execution if a CSV file contains payloads like `$(command)`. Additionally, the `cmd_distribution` function is currently broken due to a bug where shell variables (e.g., `$bins`) are placed inside a quoted Python heredoc, preventing their expansion. While these appear to be unintentional coding flaws rather than deliberate malice, the RCE risk via CSV processing warrants a suspicious classification.
Capability Assessment
Purpose & Capability
Name/description (terminal ASCII charts, CSV/JSON processing) match the provided script and SKILL.md. Declared optional DATAVIZ_DIR and use of python3/bash are reasonable for the stated capabilities.
Instruction Scope
Runtime instructions limit actions to reading user-supplied CSV/JSON files, producing terminal visualizations/exports, and writing a local data directory/history log. The SKILL.md and script do not attempt to read unrelated system credentials or send data to external endpoints.
Install Mechanism
No install spec; the skill is instruction + a bundled shell script. No external downloads or package installations are performed by the skill itself.
Credentials
The skill requests no secrets and uses only standard environment vars (DATAVIZ_DIR, XDG_DATA_HOME, HOME). It creates and writes under a per-user data directory (~/.local/share/data-visualizer) and logs history there — expected for this type of tool but worth noting for privacy-conscious users.
Persistence & Privilege
always is false and the skill does not request elevated or cross-skill configuration. It creates and uses its own data directory/history log (normal for a CLI tool).
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install data-visualizer
  3. After installation, invoke the skill by name or use /data-visualizer
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v3.0.1
test
v3.0.0
v3.0.0: All 16 commands fully implemented (heatmap, matrix, correlate, normalize, pivot, from-json, to-svg, to-html).
v2.1.5
v2.1.5: Fixed unsafe Python heredocs, accurate ASCII chart description.
v2.1.4
v2.1.4: Fix config paths and dependency declarations.
v2.1.3
v2.1.3: SKILL.md accurately describes ASCII terminal visualizations, no SVG/HTML claims.
v2.1.2
v2.1.2: SKILL.md from script help output
v2.1.0
v2.1.0: SKILL.md rewritten to match script.sh commands exactly.
v2.0.3
update
v2.0.2
Fix VT: remove old skeleton scripts, align SKILL.md
v2.0.1
SKILL.md aligned with script.sh for moderation fix
v2.0.0
v2.5 standard: Use-when desc, homepage, source, security fix
v2.3.4
yaml-fix+quality
v2.3.3
yaml-fix+quality
v2.3.2
Quality upgrade
v2.4.0
Major upgrade: custom commands and real functionality
v2.3.1
Quality update: docs, examples, standards compliance
v2.3.0
Quality fixes: aligned docs with implementation
v2.2.0
Enhanced descriptions for better AI triggering
v1.0.2
Runtime fix
v1.0.1
- Removed the tips.md file. - No changes to functionality or documentation in SKILL.md.
Metadata
Slug data-visualizer
Version 3.0.1
License MIT-0
All-time Installs 16
Active Installs 15
Total Versions 21
Frequently Asked Questions

What is Data Visualizer?

Terminal ASCII chart toolkit. Create bar charts, sparklines, histograms, and gauges from CSV or JSON data in the terminal. It is an AI Agent Skill for Claude Code / OpenClaw, with 1058 downloads so far.

How do I install Data Visualizer?

Run "/install data-visualizer" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Data Visualizer free?

Yes, Data Visualizer is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Data Visualizer support?

Data Visualizer is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Data Visualizer?

It is built and maintained by bytesagain4 (@xueyetianya); the current version is v3.0.1.

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