Markdansi — AI Tool by steipete

by steipete · AI Tool · ★ 52

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

About Markdansi

🎨 Markdansi: Wraps, colors, links—no baggage. Tiny, dependency-light Markdown → ANSI renderer and CLI for modern Node (=22). Focuses on readable terminal output with sensible wrapping, GFM support (tables, task lists, strikethrough), optional OSC‑8 hyperlinks, and zero built‑in syntax highlighting (pluggable hook). Written in TypeScript, ships ESM. Published on npm as . Install Grab it from npm; no native deps, so install is instant on Node 22+. CLI Quick one-shot renderer: pipe Markdown in, ANSI comes out. Flags let you pick width, wrap, colors, links, and table/list styling. Input: positional , , or stdin when neither is given (use for stdin explicitly). Output: stdout unless provided. Wrapping: on by default; disables hard wrapping. Links: OSC‑8 when supported; disables. Lists/

ansiimarkdowntypescript

Quick Facts

Stars52
Forks8
LanguageTypeScript
CategoryAI Tool
LicenseMIT
Quality Score68.6617922728993/100
Last Updated2026-07-01
Created2025-11-16
Platformsnode
Est. Tokens~15k

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Frequently Asked Questions

What is Markdansi?

Markdansi is Markdown to ANSII in TypeScript based on Micro-Mark, with support for URLs, tables, lists and more.. It is categorized as a AI Tool with 52 GitHub stars.

What programming language is Markdansi written in?

Markdansi is primarily written in TypeScript. It covers topics such as ansii, markdown, typescript.

How do I install or use Markdansi?

You can find installation instructions and usage details in the Markdansi GitHub repository at github.com/steipete/Markdansi. The project has 52 stars and 8 forks, indicating an active community.

What license does Markdansi use?

Markdansi is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to Markdansi?

The top alternatives to Markdansi on Agent Skills Hub include multi-model-chat, langchainjs-mcp-adapters, claudex. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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