skills-collection-manager
Comprehensive toolkit for managing large Claude Code skill collections including bulk downloading from GitHub, organizing into categories, detecting and removing duplicates, consolidating skills, and maintaining clean skill repositories with 100+ skills.
What this skill does
# Skills Collection Manager
Efficiently manage, organize, and maintain large collections of Claude Code skills at scale.
## Overview
As skill collections grow to hundreds of entries, manual management becomes impractical. This skill provides automated tools and workflows for:
- Bulk downloading skills from GitHub repositories
- Organizing skills into logical categories
- Detecting and removing duplicates
- Consolidating similar skills
- Maintaining repository health
- Generating documentation and indexes
## When to Use
Use this skill when:
- Managing 50+ skills in a collection
- Importing skills from multiple GitHub repositories
- Organizing an unstructured skill directory
- Identifying duplicate or redundant skills
- Creating team-wide skill libraries
- Maintaining organizational skill repositories
- Building curated skill collections
- Auditing skill quality and coverage
## Directory Structure Patterns
### Pattern 1: Flat Structure
```
skills/
├── docker-helper/
│ └── SKILL.md
├── kubernetes-deploy/
│ └── SKILL.md
├── postgres-optimization/
│ └── SKILL.md
└── ...
```
**Pros**: Simple, easy to navigate
**Cons**: Hard to manage at scale (100+ skills)
### Pattern 2: Categorized Structure
```
skills/
├── automation/
│ ├── skill-harvester/
│ │ └── SKILL.md
│ └── workflow-automation/
│ └── SKILL.md
├── backend/
│ ├── api-design/
│ │ └── SKILL.md
│ └── database-optimization/
│ └── SKILL.md
├── devops/
│ ├── docker-optimization/
│ │ └── SKILL.md
│ └── kubernetes-deploy/
│ └── SKILL.md
└── ...
```
**Pros**: Organized, scalable
**Cons**: Requires categorization logic
### Pattern 3: Hybrid Structure
```
skills/ # Flat for easy access
skills-by-category/ # Organized for browsing
duplicates/ # Quarantine area
archived/ # Old/deprecated skills
```
**Pros**: Best of both worlds
**Cons**: More complex to maintain
## Bulk Skill Download
### Download from GitHub Repository
```bash
#!/bin/bash
# bulk-download-skills.sh - Download skills from GitHub repos
REPOS_FILE="${1:-repos.txt}"
OUTPUT_DIR="downloaded-skills"
CHECKPOINT="download-checkpoint.txt"
# Create repos list if it doesn't exist
if [ ! -f "$REPOS_FILE" ]; then
cat > "$REPOS_FILE" << EOF
https://github.com/anthropics/claude-code-skills
https://github.com/user/custom-skills
https://github.com/team/shared-skills
EOF
echo "Created example $REPOS_FILE - edit and run again"
exit 0
fi
mkdir -p "$OUTPUT_DIR"
# Process repos in batches
while read -r repo_url; do
# Skip comments and empty lines
[[ "$repo_url" =~ ^# ]] && continue
[[ -z "$repo_url" ]] && continue
# Check if already downloaded
if grep -q "$repo_url" "$CHECKPOINT" 2>/dev/null; then
echo "✓ Skipping $repo_url (already downloaded)"
continue
fi
echo "=== Downloading: $repo_url ==="
# Extract repo name
REPO_NAME=$(basename "$repo_url" .git)
TEMP_DIR=$(mktemp -d)
# Clone with timeout
if timeout 60s git clone --depth 1 "$repo_url" "$TEMP_DIR" 2>/dev/null; then
# Find and copy skill files
SKILLS_FOUND=0
# Look for skills in common locations
for PATTERN in "skills/*/SKILL.md" "skills/**/skill.md" ".claude/skills/*/SKILL.md"; do
find "$TEMP_DIR" -path "*/$PATTERN" 2>/dev/null | while read skill_file; do
# Extract skill name (parent directory)
SKILL_NAME=$(basename $(dirname "$skill_file"))
DEST_DIR="$OUTPUT_DIR/${REPO_NAME}/${SKILL_NAME}"
mkdir -p "$DEST_DIR"
cp "$skill_file" "$DEST_DIR/"
# Copy additional files if present
SKILL_DIR=$(dirname "$skill_file")
cp "$SKILL_DIR"/*.md "$DEST_DIR/" 2>/dev/null || true
cp "$SKILL_DIR"/*.yaml "$DEST_DIR/" 2>/dev/null || true
cp "$SKILL_DIR"/*.json "$DEST_DIR/" 2>/dev/null || true
SKILLS_FOUND=$((SKILLS_FOUND + 1))
echo " ✓ Copied: $SKILL_NAME"
done
done
if [ $SKILLS_FOUND -gt 0 ]; then
echo "$repo_url" >> "$CHECKPOINT"
echo "✓ Downloaded $SKILLS_FOUND skills from $REPO_NAME"
else
echo "⚠️ No skills found in $REPO_NAME"
fi
rm -rf "$TEMP_DIR"
else
echo "✗ Failed to clone $repo_url"
fi
echo ""
done < "$REPOS_FILE"
# Summary
TOTAL_SKILLS=$(find "$OUTPUT_DIR" -name "SKILL.md" -o -name "skill.md" | wc -l)
echo "=== Download Complete ==="
echo "Total skills downloaded: $TOTAL_SKILLS"
echo "Output directory: $OUTPUT_DIR"
```
### Batch Download Script
```bash
#!/bin/bash
# download-top-repos.sh - Download skills from popular repositories
# Top Claude Code skill repositories
REPOS=(
"https://github.com/anthropics/claude-code-skills"
"https://github.com/works/claude-code-skills"
"https://github.com/jonbaker99/my-claude-code-skills"
"https://github.com/diet103/my_claude_skills"
"https://github.com/mrgoonie/my-claude-code-skills"
)
BATCH_SIZE=5
PROCESSED=0
for repo in "${REPOS[@]}"; do
echo "$repo" >> repos-batch.txt
PROCESSED=$((PROCESSED + 1))
# Process in batches to avoid timeouts
if [ $((PROCESSED % BATCH_SIZE)) -eq 0 ]; then
./bulk-download-skills.sh repos-batch.txt
rm repos-batch.txt
echo "Batch complete. Continuing..."
sleep 2
fi
done
# Process remaining
if [ -f repos-batch.txt ]; then
./bulk-download-skills.sh repos-batch.txt
rm repos-batch.txt
fi
```
## Skill Organization
### Auto-Categorization
```bash
#!/bin/bash
# categorize-skills.sh - Auto-categorize skills based on content
SKILLS_DIR="${1:-skills}"
OUTPUT_DIR="skills-by-category"
# Category mapping based on keywords
declare -A CATEGORIES=(
["docker|container|kubernetes|k8s"]="infrastructure"
["api|endpoint|rest|graphql|backend"]="backend"
["react|vue|angular|frontend|ui|component"]="frontend"
["test|testing|jest|pytest|mocha"]="testing"
["ci|cd|deploy|github.action|jenkins"]="devops"
["database|postgres|mysql|mongodb|sql"]="databases"
["auth|authentication|jwt|oauth|security"]="security"
["aws|azure|gcp|cloud|serverless"]="cloud"
["python|javascript|typescript|golang|rust"]="development"
["doc|documentation|readme|markdown"]="documentation"
)
mkdir -p "$OUTPUT_DIR"
# Process each skill
find "$SKILLS_DIR" -name "SKILL.md" -o -name "skill.md" | while read skill_file; do
SKILL_NAME=$(basename $(dirname "$skill_file"))
SKILL_CONTENT=$(cat "$skill_file" | tr '[:upper:]' '[:lower:]')
echo "Processing: $SKILL_NAME"
# Try to match category
MATCHED_CATEGORY=""
for pattern in "${!CATEGORIES[@]}"; do
if echo "$SKILL_CONTENT" | grep -qE "$pattern"; then
MATCHED_CATEGORY="${CATEGORIES[$pattern]}"
break
fi
done
# Default category if no match
if [ -z "$MATCHED_CATEGORY" ]; then
MATCHED_CATEGORY="uncategorized"
fi
# Copy to categorized directory
DEST_DIR="$OUTPUT_DIR/$MATCHED_CATEGORY/$SKILL_NAME"
mkdir -p "$DEST_DIR"
cp -r "$(dirname $skill_file)"/* "$DEST_DIR/"
echo " → $MATCHED_CATEGORY"
done
# Generate summary
echo ""
echo "=== Categorization Summary ==="
for category_dir in "$OUTPUT_DIR"/*; do
CATEGORY=$(basename "$category_dir")
COUNT=$(find "$category_dir" -name "SKILL.md" -o -name "skill.md" | wc -l)
printf "%-20s : %3d skills\n" "$CATEGORY" "$COUNT"
done
```
### Manual Reorganization
```bash
#!/bin/bash
# reorganize-skills.sh - Interactive skill reorganization
SKILLS_DIR="skills"
CATEGORIES=("automation" "backend" "cloud" "data-engineering" "devops" "documentation" "frontend" "infrastructure" "security" "testing")
# Show uncategorized skills
echo "=== Uncategorized Skills ==="
find "$SKILLS_DIR" -maxdepth 1 -type d | tail -n +2 | while read skill_dir; do
SKILL_NAME=$(basename "$skilRelated in AI Agents
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