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AGENT SKILL

tapestry

tapestry 是面向效率工具、数据与分析、内容与媒体的 Agent Skill,来自 michalparkola/tapestry-skills-for-claude-code。查看技能说明、操作步骤与使用约定,并通过原项目了解详细用法。

Unified content extraction and action planning. Use when user says "tapestry <URL>", "weave <URL>", "help me plan <URL>", "extract and plan <URL>", "make this actionable <URL>", or similar phrases indicating they want to extract content and create an action plan. Automatically detects content type (YouTube video, article, PDF) and processes accordingly.

SKILL.md

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nametapestry
descriptionUnified content extraction and action planning. Use when user says "tapestry <URL>", "weave <URL>", "help me plan <URL>", "extract and plan <URL>", "make this actionable <URL>", or similar phrases indicating they want to extract content and create an action plan. Automatically detects content type (YouTube video, article, PDF) and processes accordingly.
allowed-toolsBash,Read,Write

Tapestry: Unified Content Extraction + Action Planning

This is the master skill that orchestrates the entire Tapestry workflow: 1. Detect content type from URL 2. Extract content using appropriate skill 3. Automatically create a Ship-Learn-Next action plan

When to Use This Skill

Activate when the user: - Says "tapestry [URL]" - Says "weave [URL]" - Says "help me plan [URL]" - Says "extract and plan [URL]" - Says "make this actionable [URL]" - Says "turn [URL] into a plan" - Provides a URL and asks to "learn and implement from this" - Wants the full Tapestry workflow (extract → plan)

Keywords to watch for: tapestry, weave, plan, actionable, extract and plan, make a plan, turn into action

How It Works

Complete Workflow:

  1. Detect URL type (YouTube, article, PDF)
  2. Extract content using appropriate skill: - YouTube → youtube-transcript skill - Article → article-extractor skill - PDF → download and extract text
  3. Create action plan using ship-learn-next skill
  4. Save both content file and plan file
  5. Present summary to user

URL Detection Logic

YouTube Videos

Patterns to detect: - youtube.com/watch?v= - youtu.be/ - youtube.com/shorts/ - m.youtube.com/watch?v=

Action: Use youtube-transcript skill

Web Articles/Blog Posts

Patterns to detect: - http:// or https:// - NOT YouTube, NOT PDF - Common domains: medium.com, substack.com, dev.to, etc. - Any HTML page

Action: Use article-extractor skill

PDF Documents

Patterns to detect: - URL ends with .pdf - URL returns Content-Type: application/pdf

Action: Download and extract text

Other Content

Fallback: - Try article-extractor (works for most HTML) - If fails, inform user of unsupported type

Step-by-Step Workflow

Step 1: Detect Content Type

URL="$1"

# Check for YouTube
if [[ "$URL" =~ youtube\.com/watch || "$URL" =~ youtu\.be/ || "$URL" =~ youtube\.com/shorts ]]; then
    CONTENT_TYPE="youtube"

# Check for PDF
elif [[ "$URL" =~ \.pdf$ ]]; then
    CONTENT_TYPE="pdf"

# Check if URL returns PDF
elif curl -sI "$URL" | grep -i "Content-Type: application/pdf" > /dev/null; then
    CONTENT_TYPE="pdf"

# Default to article
else
    CONTENT_TYPE="article"
fi

echo "📍 Detected: $CONTENT_TYPE"

Step 2: Extract Content (by Type)

YouTube Video

# Use youtube-transcript skill workflow
echo "📺 Extracting YouTube transcript..."

# 1. Check for yt-dlp
if ! command -v yt-dlp &> /dev/null; then
    echo "Installing yt-dlp..."
    brew install yt-dlp
fi

# 2. Get video title
VIDEO_TITLE=$(yt-dlp --print "%(title)s" "$URL" | tr '/' '_' | tr ':' '-' | tr '?' '' | tr '"' '')

# 3. Download transcript
yt-dlp --write-auto-sub --skip-download --sub-langs en --output "temp_transcript" "$URL"

# 4. Convert to clean text (deduplicate)
python3 -c "
import sys, re
seen = set()
vtt_file = 'temp_transcript.en.vtt'
try:
    with open(vtt_file, 'r') as f:
        for line in f:
            line = line.strip()
            if line and not line.startswith('WEBVTT') and not line.startswith('Kind:') and not line.startswith('Language:') and '-->' not in line:
                clean = re.sub('<[^>]*>', '', line)
                clean = clean.replace('&amp;', '&').replace('&gt;', '>').replace('&lt;', '<')
                if clean and clean not in seen:
                    print(clean)
                    seen.add(clean)
except FileNotFoundError:
    print('Error: Could not find transcript file', file=sys.stderr)
    sys.exit(1)
" > "${VIDEO_TITLE}.txt"

# 5. Cleanup
rm -f temp_transcript.en.vtt

CONTENT_FILE="${VIDEO_TITLE}.txt"
echo "✓ Saved transcript: $CONTENT_FILE"

Article/Blog Post

# Use article-extractor skill workflow
echo "📄 Extracting article content..."

# 1. Check for extraction tools
if command -v reader &> /dev/null; then
    TOOL="reader"
elif command -v trafilatura &> /dev/null; then
    TOOL="trafilatura"
else
    TOOL="fallback"
fi

echo "Using: $TOOL"

# 2. Extract based on tool
case $TOOL in
    reader)
        reader "$URL" > temp_article.txt
        ARTICLE_TITLE=$(head -n 1 temp_article.txt | sed 's/^# //')
        ;;

    trafilatura)
        METADATA=$(trafilatura --URL "$URL" --json)
        ARTICLE_TITLE=$(echo "$METADATA" | python3 -c "import json, sys; print(json.load(sys.stdin).get('title', 'Article'))")
        trafilatura --URL "$URL" --output-format txt --no-comments > temp_article.txt
        ;;

    fallback)
        ARTICLE_TITLE=$(curl -s "$URL" | grep -oP '<title>\K[^<]+' | head -n 1)
        ARTICLE_TITLE=${ARTICLE_TITLE%% - *}
        curl -s "$URL" | python3 -c "
from html.parser import HTMLParser
import sys

class ArticleExtractor(HTMLParser):
    def __init__(self):
        super().__init__()
        self.content = []
        self.skip_tags = {'script', 'style', 'nav', 'header', 'footer', 'aside', 'form'}
        self.in_content = False

    def handle_starttag(self, tag, attrs):
        if tag not in self.skip_tags and tag in {'p', 'article', 'main'}:
            self.in_content = True

    def handle_data(self, data):
        if self.in_content and data.strip():
            self.content.append(data.strip())

    def get_content(self):
        return '\n\n'.join(self.content)

parser = ArticleExtractor()
parser.feed(sys.stdin.read())
print(parser.get_content())
" > temp_article.txt
        ;;
esac

# 3. Clean filename
FILENAME=$(echo "$ARTICLE_TITLE" | tr '/' '-' | tr ':' '-' | tr '?' '' | tr '"' '' | cut -c 1-80 | sed 's/ *$//')
CONTENT_FILE="${FILENAME}.txt"
mv temp_article.txt "$CONTENT_FILE"

echo "✓ Saved article: $CONTENT_FILE"

PDF Document

# Download and extract PDF
echo "📑 Downloading PDF..."

# 1. Download PDF
PDF_FILENAME=$(basename "$URL")
curl -L -o "$PDF_FILENAME" "$URL"

# 2. Extract text using pdftotext (if available)
if command -v pdftotext &> /dev/null; then
    pdftotext "$PDF_FILENAME" temp_pdf.txt
    CONTENT_FILE="${PDF_FILENAME%.pdf}.txt"
    mv temp_pdf.txt "$CONTENT_FILE"
    echo "✓ Extracted text from PDF: $CONTENT_FILE"

    # Optionally keep PDF
    echo "Keep original PDF? (y/n)"
    read -r KEEP_PDF
    if [[ ! "$KEEP_PDF" =~ ^[Yy]$ ]]; then
        rm "$PDF_FILENAME"
    fi
else
    # No pdftotext available
    echo "⚠️  pdftotext not found. PDF downloaded but not extracted."
    echo "   Install with: brew install poppler"
    CONTENT_FILE="$PDF_FILENAME"
fi

Step 3: Create Ship-Learn-Next Action Plan

IMPORTANT: Always create an action plan after extracting content.

# Read the extracted content
CONTENT_FILE="[from previous step]"

# Invoke ship-learn-next skill logic:
# 1. Read the content file
# 2. Extract core actionable lessons
# 3. Create 5-rep progression plan
# 4. Save as: Ship-Learn-Next Plan - [Quest Title].md

# See ship-learn-next/SKILL.md for full details

Key points for plan creation: - Extract actionable lessons (not just summaries) - Define a specific 4-8 week quest - Create Rep 1 (shippable this week) - Design Reps 2-5 (progressive iterations) - Save plan to markdown file - Use format: Ship-Learn-Next Plan - [Brief Quest Title].md

Step 4: Present Results

Show user:

✅ Tapestry Workflow Complete!

📥 Content Extracted:
   ✓ [Content type]: [Title]
   ✓ Saved to: [filename.txt]
   ✓ [X] words extracted

📋 Action Plan Created:
   ✓ Quest: [Quest title]
   ✓ Saved to: Ship-Learn-Next Plan - [Title].md

🎯 Your Quest: [One-line summary]

📍 Rep 1 (This Week): [Rep 1 goal]

When will you ship Rep 1?

Complete Tapestry Workflow Script

#!/bin/bash

# Tapestry: Extract content + create action plan
# Usage: tapestry <URL>

URL="$1"

if [ -z "$URL" ]; then
    echo "Usage: tapestry <URL>"
    exit 1
fi

echo "🧵 Tapestry Workflow Starting..."
echo "URL: $URL"
echo ""

# Step 1: Detect content type
if [[ "$URL" =~ youtube\.com/watch || "$URL" =~ youtu\.be/ || "$URL" =~ youtube\.com/shorts ]]; then
    CONTENT_TYPE="youtube"
elif [[ "$URL" =~ \.pdf$ ]] || curl -sI "$URL" | grep -iq "Content-Type: application/pdf"; then
    CONTENT_TYPE="pdf"
else
    CONTENT_TYPE="article"
fi

echo "📍 Detected: $CONTENT_TYPE"
echo ""

# Step 2: Extract content
case $CONTENT_TYPE in
    youtube)
        echo "📺 Extracting YouTube transcript..."
        # [YouTube extraction code from above]
        ;;

    article)
        echo "📄 Extracting article..."
        # [Article extraction code from above]
        ;;

    pdf)
        echo "📑 Downloading PDF..."
        # [PDF extraction code from above]
        ;;
esac

echo ""

# Step 3: Create action plan
echo "🚀 Creating Ship-Learn-Next action plan..."
# [Plan creation using ship-learn-next skill]

echo ""
echo "✅ Tapestry Workflow Complete!"
echo ""
echo "📥 Content: $CONTENT_FILE"
echo "📋 Plan: Ship-Learn-Next Plan - [title].md"
echo ""
echo "🎯 Next: Review your action plan and ship Rep 1!"

Error Handling

Common Issues:

1. Unsupported URL type - Try article extraction as fallback - If fails: "Could not extract content from this URL type"

2. No content extracted - Check if URL is accessible - Try alternate extraction method - Inform user: "Extraction failed. URL may require authentication."

3. Tools not installed - Auto-install when possible (yt-dlp, reader, trafilatura) - Provide install instructions if auto-install fails - Use fallback methods when available

4. Empty or invalid content - Verify file has content before creating plan - Don't create plan if extraction failed - Show preview to user before planning

Best Practices

  • ✅ Always show what was detected ("📍 Detected: youtube")
  • ✅ Display progress for each step
  • ✅ Save both content file AND plan file
  • ✅ Show preview of extracted content (first 10 lines)
  • ✅ Create plan automatically (don't ask)
  • ✅ Present clear summary at end
  • ✅ Ask commitment question: "When will you ship Rep 1?"

Usage Examples

Example 1: YouTube Video (using "tapestry")

User: tapestry https://www.youtube.com/watch?v=dQw4w9WgXcQ

Claude:
🧵 Tapestry Workflow Starting...
📍 Detected: youtube
📺 Extracting YouTube transcript...
✓ Saved transcript: Never Gonna Give You Up.txt

🚀 Creating action plan...
✓ Quest: Master Video Production
✓ Saved plan: Ship-Learn-Next Plan - Master Video Production.md

✅ Complete! When will you ship Rep 1?

Example 2: Article (using "weave")

User: weave https://example.com/how-to-build-saas

Claude:
🧵 Tapestry Workflow Starting...
📍 Detected: article
📄 Extracting article...
✓ Using reader (Mozilla Readability)
✓ Saved article: How to Build a SaaS.txt

🚀 Creating action plan...
✓ Quest: Build a SaaS MVP
✓ Saved plan: Ship-Learn-Next Plan - Build a SaaS MVP.md

✅ Complete! When will you ship Rep 1?

Example 3: PDF (using "help me plan")

User: help me plan https://example.com/research-paper.pdf

Claude:
🧵 Tapestry Workflow Starting...
📍 Detected: pdf
📑 Downloading PDF...
✓ Downloaded: research-paper.pdf
✓ Extracted text: research-paper.txt

🚀 Creating action plan...
✓ Quest: Apply Research Findings
✓ Saved plan: Ship-Learn-Next Plan - Apply Research Findings.md

✅ Complete! When will you ship Rep 1?

Dependencies

This skill orchestrates the other skills, so requires:

For YouTube: - yt-dlp (auto-installed) - Python 3 (for deduplication)

For Articles: - reader (npm) OR trafilatura (pip) - Falls back to basic curl if neither available

For PDFs: - curl (built-in) - pdftotext (optional - from poppler package) - Install: brew install poppler (macOS) - Install: apt install poppler-utils (Linux)

For Planning: - No additional requirements (uses built-in tools)

Philosophy

Tapestry weaves learning content into action.

The unified workflow ensures you never just consume content - you always create an implementation plan. This transforms passive learning into active building.

Extract → Plan → Ship → Learn → Next.

That's the Tapestry way.

来源:michalparkola/tapestry-skills-for-claude-code · MIT 许可 · 许可原文 · MD 为来源页保存的历史版本