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file-converter

maintained by aiskillstore

star 124 account_tree 6 verified_user MIT License
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name: file-converter description: This skill handles file format conversions across documents (PDF, DOCX, Markdown, HTML, TXT), data files (JSON, CSV, YAML, XML, TOML), and images (PNG, JPG, WebP, SVG, GIF). Use when the user requests converting, transforming, or exporting files between formats. Generates conversion code dynamically based on the specific request. author: Joseph OBrien status: unpublished updated: '2025-12-23' version: 1.0.1 tag: skill type: skill

File Converter

Overview

Convert files between formats across three categories: documents, data files, and images. Generate Python code dynamically for each conversion request, selecting appropriate libraries and handling edge cases.

Conversion Categories

Documents

From To Recommended Library
Markdown HTML markdown or mistune
HTML Markdown markdownify or html2text
HTML PDF weasyprint or pdfkit (requires wkhtmltopdf)
PDF Text pypdf or pdfplumber
DOCX Markdown mammoth
DOCX PDF docx2pdf (Windows/macOS) or LibreOffice CLI
Markdown PDF Convert via HTML first, then to PDF

Data Files

From To Recommended Library
JSON YAML pyyaml
YAML JSON pyyaml
JSON CSV pandas or stdlib csv + json
CSV JSON pandas or stdlib csv + json
JSON TOML tomli/tomllib (read) + tomli-w (write)
XML JSON xmltodict
JSON XML dicttoxml or xmltodict.unparse

Images

From To Recommended Library
PNG/JPG/WebP/GIF Any raster Pillow (PIL)
SVG PNG/JPG cairosvg or svglib + reportlab
PNG SVG potrace (CLI) for tracing, limited fidelity

Workflow

  1. Identify source format (from file extension or user statement)
  2. Identify target format
  3. Check references/ for format-specific guidance
  4. Generate conversion code using recommended library
  5. Handle edge cases (encoding, transparency, nested structures)
  6. Execute conversion and report results

Quick Patterns

Data: JSON to YAML

import json
import yaml

with open("input.json") as f:
    data = json.load(f)

with open("output.yaml", "w") as f:
    yaml.dump(data, f, default_flow_style=False, allow_unicode=True)

Data: CSV to JSON

import csv
import json

with open("input.csv") as f:
    reader = csv.DictReader(f)
    data = list(reader)

with open("output.json", "w") as f:
    json.dump(data, f, indent=2)

Document: Markdown to HTML

import markdown

with open("input.md") as f:
    md_content = f.read()

html = markdown.markdown(md_content, extensions=["tables", "fenced_code"])

with open("output.html", "w") as f:
    f.write(html)

Image: PNG to WebP

from PIL import Image

img = Image.open("input.png")
img.save("output.webp", "WEBP", quality=85)

Image: SVG to PNG

import cairosvg

cairosvg.svg2png(url="input.svg", write_to="output.png", scale=2)

Resources

Detailed guidance for complex conversions is in references/:

  • references/document-conversions.md - PDF handling, encoding issues, styling preservation
  • references/data-conversions.md - Schema handling, type coercion, nested structures
  • references/image-conversions.md - Quality settings, transparency, color profiles

Consult these references when handling edge cases or when the user has specific quality/fidelity requirements.

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Skill Details

GitHub Stars 124
GitHub Forks 6
Created Jan 2026
Last Updated 4个月前
tools tools productivity tools

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