菜单
Convert mọi file (PDF, Word, Excel, PowerPoint, Image, Audio, HTML, CSV, YouTube URL) thành Markdown cho LLM. Tích hợp vào YAMTAM vault để import tài liệu.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/yanacuti1121/Yana-AI --skill markitdown命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Sovereign-grade safety OS for AI coding agents. 62 hooks, 2,025 skills, L1 memory, circuit breakers, and cross-engine enforcement — blocks rm -rf, force push, pipe-to-shell, and 40+ attack vectors before they reach your repo.
Use when the user wants to generate or keep repository documentation up to date via OpenWiki (langchain-ai/openwiki) — an LLM-driven CLI that writes a wiki for a codebase (or a personal knowledge base from Notion/Gmail/Slack/X/web search) and keeps it fresh via a scheduled CI pull request. Examples: "set up OpenWiki for this repo", "keep the docs updated automatically", "generate an agent wiki".
Use when implementing the core AR pipeline (camera pose estimation, marker tracking, projection overlay) from first principles — not when just using ARKit/ARCore/Unity's AR framework as a black box. Triggers on: 'build augmented reality from scratch', 'marker-based AR tracking', 'camera pose estimation', 'implement fiducial marker detection', 'AR projection matrix math', 'markerless AR tracking'. Covers marker-based vs markerless tracking, pose estimation, and the projection math to overlay 3D content on a camera feed.
基于 SOC 职业分类
正在显示 SKILL.md
| name | markitdown |
| description | Convert mọi file (PDF, Word, Excel, PowerPoint, Image, Audio, HTML, CSV, YouTube URL) thành Markdown cho LLM. Tích hợp vào YAMTAM vault để import tài liệu. |
| triggers | ["markitdown","convert file to markdown","pdf to markdown","word to markdown","import document","import pdf","đọc file pdf","convert tài liệu","vault import","đưa file vào vault"] |
Source: github.com/microsoft/markitdown
Version: 0.1.6 (installed)
License: MIT · Built by Microsoft AutoGen team
| Format | Notes |
|---|---|
| Text extraction | |
| Word (.docx) | Full structure |
| PowerPoint (.pptx) | Slides → Markdown |
| Excel (.xlsx) | Tables |
| Image | EXIF + OCR (với LLM) |
| Audio | Transcription |
| HTML | Clean text |
| CSV / JSON / XML | Structured |
| YouTube URL | Transcript tự động |
| EPub | Chapters |
from markitdown import MarkItDown
md = MarkItDown()
# Convert file
result = md.convert("document.pdf")
print(result.text_content)
# Convert URL
result = md.convert("https://example.com")
# Convert YouTube → transcript
result = md.convert("https://youtube.com/watch?v=xxx")
markitdown document.pdf > output.md
markitdown document.pdf -o output.md
markitdown https://example.com -o page.md
# Import PDF vào vault
python3 tools/vault-import.py document.pdf
# Import thư mục
python3 tools/vault-import.py --dir ./docs/ --ext pdf,docx
# Import + ghi vào knowledge base
python3 tools/vault-import.py report.pdf --tag bao-cao --lang vi
import anthropic
from markitdown import MarkItDown
client = anthropic.Anthropic()
md = MarkItDown(llm_client=client, llm_model="claude-haiku-4-5-20251001")
result = md.convert("scan_bai_thi.jpg")
print(result.text_content)