# shift-labs-ai/markit

🖍️ Convert anything to markdown. Mark it.

Repository: https://github.com/shift-labs-ai/markit
Canonical: https://ross.abutalabs.com/products/markit
Language: Rust
License: MIT
License Family: permissive
Last push: 2026-08-17T22:50:50+00:00

## Health v2 (maintenance only)
Score: 81/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 98, release rhythm 98, longevity 11
- inputs: {"age_days": 161, "days_push": 16, "days_rel": 16, "gap_med": 1.0, "n_releases_24m": 11}
- flags: young
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1315, forks 55 (observed 2026-08-28T04:04:20.655672+00:00)

## What it is
A Rust-based tool that converts documents, data files, web pages, and media into Markdown, usable both as a CLI and a library. It supports a wide range of formats including PDF, DOCX, PPTX, XLSX, HTML, EPUB, Jupyter notebooks, and URLs.

## Use cases
- convert pdf to markdown
- convert docx to markdown
- extract text from pdf for llm
- convert html page to markdown
- convert excel spreadsheet to markdown table
- batch convert documents to markdown
- extract content from epub

## When to choose
- you need fast, dependency-light document-to-markdown conversion without OCR or model calls
- you want a single CLI handling many formats including PDF, Office files, and URLs
- you need markdown output for feeding documents into LLM pipelines

## When to avoid
- you need OCR for scanned PDFs with no text layer
- you need pixel-perfect layout or formatting preservation rather than markdown
- you need a GUI-based conversion workflow

## Facets
- artifact type: cli-tool
- maturity: active
- function: parser, pdf, markdown, cli, ocr, web-scraping
- domain: developer-tools, pdf, files
- platform: cli, cross-platform, rust
- tags: document-conversion, markdown-conversion, pdf-to-markdown, file-parsing, llm-preprocessing, command-line, natural-language-processing, nodejs

## Member repositories
- shift-labs-ai/markit (main) score 81

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:20.655672+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:48:43.303664+00:00, confidence not recorded.
  - readme: https://github.com/shift-labs-ai/markit (fetched 2026-08-28T04:04:20.655672+00:00, sha 0ef8957fb64c)
- Data as of 2026-08-30T08:39:29.467469+00:00.