Token导航 LogoToken导航

Agent Skill · 研究检索

skills-collection-manager(技能收集经理)

skills-collection-manager 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

skills-collection-manager 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证为 MIT,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 44,028。

总安装 941周安装 40GitHub Stars 14下载 330核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:skills-collection-manager(技能收集经理)
来源仓库:https://github.com/jackspace/claudeskillz
仓库路径:skills/skills-collection-manager
安装命令:
npx skills add https://github.com/jackspace/claudeskillz --skill skills-collection-manager
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/jackspace/claudeskillz --skill skills-collection-manager

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息。适合在技能收集和管理场景中使用。可通过来源仓库和 README 核验具体用法。安装命令:npx skills add https://github.com/jackspace/claudeskillz --skill skills-collection-manager。

建议确认权限范围及是否会触发联网或文件读写。

来源仓库内路径:skills/skills-collection-manager

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/jackspace/claudeskillz --skill skills-collecti…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

skills-collection-manager 怎么安装?

在终端执行 npx skills add https://github.com/jackspace/claudeskillz --skill skills-collection-manager。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

skills-collection-manager 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

skills-collection-manager 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

skills-collection-manager 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

skills-collection-manager 用的人多吗?

公开数据是累计安装 941 次,近一周安装 40 次,下载 330 次,GitHub 14 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

skills-collection-manager 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
skills-collection-manager

技能收集经理 · 本页

94114调用外部服务MIT有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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

#!/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

#!/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

#!/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

#!/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 "$skill_dir")
    echo "- $SKILL_NAME"
done

echo ""
echo "Available categories:"
for i in "${!CATEGORIES[@]}"; do
    echo "$((i+1))) ${CATEGORIES[$i]}"
done

echo ""
read -p "Reorganize skills? (y/n) " -n 1 -r
echo
[[ ! $REPLY =~ ^[Yy]$ ]] && exit 0

find "$SKILLS_DIR" -maxdepth 1 -type d | tail -n +2 | while read skill_dir; do
    SKILL_NAME=$(basename "$skill_dir")

    echo ""
    echo "Skill: $SKILL_NAME"
    echo "Description: $(grep -m 1 "description:" "$skill_dir/SKILL.md" 2>/dev/null | cut -d: -f2-)"
    echo ""

    read -p "Category (1-${#CATEGORIES[@]}, s=skip): " choice

    if [[ "$choice" =~ ^[0-9]+$ ]] && [ "$choice" -ge 1 ] && [ "$choice" -le "${#CATEGORIES[@]}" ]; then
        CATEGORY="${CATEGORIES[$((choice-1))]}"
        DEST_DIR="skills-by-category/$CATEGORY/$SKILL_NAME"

        mkdir -p "$DEST_DIR"
        mv "$skill_dir"/* "$DEST_DIR/"
        rmdir "$skill_dir"

        echo "✓ Moved to $CATEGORY"
    fi
done

Duplicate Detection

Simple Duplicate Finder

#!/bin/bash
# find-duplicates.sh - Find duplicate skills

SKILLS_DIR="${1:-skills}"
DUPLICATES_DIR="duplicates"

mkdir -p "$DUPLICATES_DIR"

# Create temporary index
TEMP_INDEX=$(mktemp)

# Index all skills by normalized name
find "$SKILLS_DIR" -name "SKILL.md" -o -name "skill.md" | while read skill_file; do
    SKILL_DIR=$(dirname "$skill_file")
    SKILL_NAME=$(basename "$SKILL_DIR")

    # Normalize name (remove variations)
    NORMALIZED=$(echo "$SKILL_NAME" | tr '[:upper:]' '[:lower:]' | sed 's/[-_]//g')

    echo "$NORMALIZED|$SKILL_DIR" >> "$TEMP_INDEX"
done

# Find duplicates
cat "$TEMP_INDEX" | cut -d'|' -f1 | sort | uniq -d | while read dup_name; do
    echo "=== Duplicate: $dup_name ==="

    grep "^$dup_name|" "$TEMP_INDEX" | cut -d'|' -f2 | while read skill_dir; do
        ORIGINAL_NAME=$(basename "$skill_dir")
        echo "  - $ORIGINAL_NAME"

        # Move to duplicates folder
        DUP_DEST="$DUPLICATES_DIR/$ORIGINAL_NAME"
        if [ ! -d "$DUP_DEST" ]; then
            mv "$skill_dir" "$DUP_DEST"
            echo "    → Moved to $DUPLICATES_DIR"
        fi
    done
    echo ""
done

rm "$TEMP_INDEX"

# Summary
DUP_COUNT=$(find "$DUPLICATES_DIR" -name "SKILL.md" -o -name "skill.md" | wc -l)
echo "Found $DUP_COUNT potential duplicates in $DUPLICATES_DIR"
echo "Review and manually merge or delete"

Advanced Duplicate Detection (Content-based)

#!/usr/bin/env python3
# detect-duplicates.py - Content-based duplicate detection

import os
import re
from pathlib import Path
from difflib import SequenceMatcher
from collections import defaultdict

def normalize_content(content):
    """Normalize content for comparison"""
    # Remove frontmatter
    content = re.sub(r'^---.*?---', '', content, flags=re.DOTALL)
    # Remove whitespace and lowercase
    content = re.sub(r'\s+', ' ', content.lower())
    return content.strip()

def similarity_ratio(content1, content2):
    """Calculate similarity ratio between two contents"""
    return SequenceMatcher(None, content1, content2).ratio()

def find_duplicates(skills_dir, threshold=0.8):
    """Find skills with similar content"""
    skills = {}

    # Read all skills
    for skill_file in Path(skills_dir).rglob('SKILL.md'):
        skill_name = skill_file.parent.name
        with open(skill_file, 'r', encoding='utf-8') as f:
            content = normalize_content(f.read())
            skills[skill_name] = {
                'content': content,
                'path': str(skill_file.parent)
            }

    # Find duplicates
    duplicates = defaultdict(list)
    checked = set()

    for name1, data1 in skills.items():
        for name2, data2 in skills.items():
            if name1 == name2 or (name1, name2) in checked:
                continue

            ratio = similarity_ratio(data1['content'], data2['content'])

            if ratio >= threshold:
                duplicates[name1].append({
                    'name': name2,
                    'similarity': ratio,
                    'path': data2['path']
                })

            checked.add((name1, name2))
            checked.add((name2, name1))

    # Report findings
    if duplicates:
        print("=== Duplicate Skills Found ===\n")
        for skill, dups in duplicates.items():
            print(f"{skill}:")
            for dup in dups:
                print(f"  - {dup['name']} ({dup['similarity']:.1%} similar)")
                print(f"    Path: {dup['path']}")
            print()

        print(f"\nTotal duplicate groups: {len(duplicates)}")
    else:
        print("No duplicates found")

if __name__ == '__main__':
    import sys
    skills_dir = sys.argv[1] if len(sys.argv) > 1 else 'skills'
    threshold = float(sys.argv[2]) if len(sys.argv) > 2 else 0.8

    find_duplicates(skills_dir, threshold)

Skill Consolidation

Merge Similar Skills

#!/bin/bash
# consolidate-skills.sh - Merge similar skills

SKILL1_DIR="$1"
SKILL2_DIR="$2"
OUTPUT_NAME="$3"

if [ -z "$SKILL1_DIR" ] || [ -z "$SKILL2_DIR" ] || [ -z "$OUTPUT_NAME" ]; then
    echo "Usage: $0 <skill1-dir> <skill2-dir> <output-name>"
    exit 1
fi

OUTPUT_DIR="skills/$OUTPUT_NAME"
mkdir -p "$OUTPUT_DIR"

# Extract metadata from both skills
SKILL1_NAME=$(grep "^name:" "$SKILL1_DIR/SKILL.md" | cut -d: -f2 | xargs)
SKILL2_NAME=$(grep "^name:" "$SKILL2_DIR/SKILL.md" | cut -d: -f2 | xargs)

DESC1=$(grep "^description:" "$SKILL1_DIR/SKILL.md" | cut -d: -f2 | xargs)
DESC2=$(grep "^description:" "$SKILL2_DIR/SKILL.md" | cut -d: -f2 | xargs)

# Create consolidated skill
cat > "$OUTPUT_DIR/SKILL.md" << EOF
---
name: $OUTPUT_NAME
description: Consolidated skill combining $SKILL1_NAME and $SKILL2_NAME
consolidated-from:
  - $SKILL1_NAME
  - $SKILL2_NAME
license: MIT
---

# ${OUTPUT_NAME^}

This skill consolidates functionality from:
- **$SKILL1_NAME**: $DESC1
- **$SKILL2_NAME**: $DESC2

## From $SKILL1_NAME

$(sed -n '/^# /,$ p' "$SKILL1_DIR/SKILL.md" | tail -n +2)

---

## From $SKILL2_NAME

$(sed -n '/^# /,$ p' "$SKILL2_DIR/SKILL.md" | tail -n +2)

---

## Combined Usage

TODO: Add guidance on using consolidated functionality

EOF

echo "✓ Created consolidated skill: $OUTPUT_DIR"
echo "Review and edit: $OUTPUT_DIR/SKILL.md"

Repository Maintenance

Health Check

#!/bin/bash
# health-check.sh - Check repository health

SKILLS_DIR="${1:-skills}"

echo "=== Skills Repository Health Check ==="
echo ""

# Count total skills
TOTAL=$(find "$SKILLS_DIR" -name "SKILL.md" -o -name "skill.md" | wc -l)
echo "Total skills: $TOTAL"
echo ""

# Check for required files
echo "=== Missing Files ==="
MISSING=0
find "$SKILLS_DIR" -type d -mindepth 1 | while read skill_dir; do
    if [ ! -f "$skill_dir/SKILL.md" ] && [ ! -f "$skill_dir/skill.md" ]; then
        echo "✗ $(basename $skill_dir): No SKILL.md file"
        MISSING=$((MISSING + 1))
    fi
done
[ $MISSING -eq 0 ] && echo "✓ All skills have SKILL.md files"
echo ""

# Check for metadata
echo "=== Missing Metadata ==="
find "$SKILLS_DIR" -name "SKILL.md" -o -name "skill.md" | while read skill_file; do
    SKILL_NAME=$(basename $(dirname "$skill_file"))

    # Check for required frontmatter
    if ! grep -q "^name:" "$skill_file"; then
        echo "✗ $SKILL_NAME: Missing 'name' in frontmatter"
    fi

    if ! grep -q "^description:" "$skill_file"; then
        echo "✗ $SKILL_NAME: Missing 'description' in frontmatter"
    fi
done
echo ""

# Check for empty files
echo "=== Empty Skills ==="
find "$SKILLS_DIR" -name "SKILL.md" -o -name "skill.md" | while read skill_file; do
    if [ ! -s "$skill_file" ]; then
        echo "✗ $(basename $(dirname $skill_file)): Empty file"
    fi
done
echo ""

# Check naming conventions
echo "=== Naming Convention Issues ==="
find "$SKILLS_DIR" -type d -mindepth 1 | while read skill_dir; do
    SKILL_NAME=$(basename "$skill_dir")

    # Check for kebab-case
    if ! echo "$SKILL_NAME" | grep -qE '^[a-z0-9]+(-[a-z0-9]+)*$'; then
        echo "⚠️  $SKILL_NAME: Not in kebab-case format"
    fi
done
echo ""

echo "=== Health Check Complete ==="

Generate Documentation

#!/bin/bash
# generate-docs.sh - Generate skill collection documentation

SKILLS_DIR="${1:-skills}"
OUTPUT_FILE="SKILLS_COLLECTION_README.md"

cat > "$OUTPUT_FILE" << EOF
# Skills Collection

Auto-generated documentation for skill collection.

**Last Updated**: $(date +"%Y-%m-%d")
**Total Skills**: $(find "$SKILLS_DIR" -name "SKILL.md" -o -name "skill.md" | wc -l)

## Skills by Category

EOF

# Group by category (if using categorized structure)
if [ -d "skills-by-category" ]; then
    for category_dir in skills-by-category/*; do
        CATEGORY=$(basename "$category_dir")
        COUNT=$(find "$category_dir" -name "SKILL.md" -o -name "skill.md" | wc -l)

        echo "### ${CATEGORY^} ($COUNT)" >> "$OUTPUT_FILE"
        echo "" >> "$OUTPUT_FILE"

        find "$category_dir" -name "SKILL.md" -o -name "skill.md" | sort | while read skill_file; do
            SKILL_NAME=$(basename $(dirname "$skill_file"))
            DESC=$(grep "^description:" "$skill_file" | cut -d: -f2- | xargs)

            echo "- **$SKILL_NAME**: $DESC" >> "$OUTPUT_FILE"
        done

        echo "" >> "$OUTPUT_FILE"
    done
else
    # Flat structure
    find "$SKILLS_DIR" -name "SKILL.md" -o -name "skill.md" | sort | while read skill_file; do
        SKILL_NAME=$(basename $(dirname "$skill_file"))
        DESC=$(grep "^description:" "$skill_file" | cut -d: -f2- | xargs)

        echo "- **$SKILL_NAME**: $DESC" >> "$OUTPUT_FILE"
    done
fi

echo "✓ Generated: $OUTPUT_FILE"

Best Practices

✅ DO

  1. Categorize consistently - Use standard categories across team
  2. Check for duplicates regularly before adding new skills
  3. Maintain metadata - Ensure all skills have proper frontmatter
  4. Document changes - Keep CHANGELOG or version history
  5. Use naming conventions - kebab-case for all skill names
  6. Version control - Commit frequently with clear messages
  7. Test skills - Verify skills work before adding to collection
  8. Review regularly - Audit collection health monthly

❌ DON'T

  1. Don't mix formats - Keep consistent SKILL.md naming
  2. Don't duplicate - Search before creating new skills
  3. Don't leave orphans - Remove skills properly (don't just delete files)
  4. Don't skip descriptions - Every skill needs clear description
  5. Don't over-categorize - Keep category tree shallow (1-2 levels)
  6. Don't hoard - Archive or delete truly obsolete skills
  7. Don't ignore errors - Fix health check issues promptly

Workflows

Weekly Maintenance

#!/bin/bash
# weekly-maintenance.sh

echo "=== Weekly Skills Collection Maintenance ==="

# 1. Health check
./health-check.sh skills

# 2. Find duplicates
./find-duplicates.sh skills

# 3. Update documentation
./generate-docs.sh skills

# 4. Commit changes
git add .
git commit -m "chore: Weekly skills collection maintenance"

echo "✓ Maintenance complete"

New Skills Integration

#!/bin/bash
# integrate-new-skills.sh

NEW_SKILLS_DIR="$1"

# 1. Check for duplicates against existing
echo "Checking for duplicates..."
# ... duplicate check logic ...

# 2. Auto-categorize
echo "Categorizing new skills..."
./categorize-skills.sh "$NEW_SKILLS_DIR"

# 3. Move to main collection
echo "Integrating into collection..."
cp -r "$NEW_SKILLS_DIR"/* skills/

# 4. Update docs
./generate-docs.sh

echo "✓ Integration complete"

Version: 1.0.0 Author: Harvested from your_claude_skills repository (270+ skills managed) Last Updated: 2025-11-18 License: MIT

Quick Reference

# Download skills from GitHub repos
./bulk-download-skills.sh repos.txt

# Auto-categorize skills
./categorize-skills.sh skills/

# Find duplicates
./find-duplicates.sh skills/

# Run health check
./health-check.sh skills/

# Generate documentation
./generate-docs.sh skills/

# Weekly maintenance
./weekly-maintenance.sh

Scale your skill collection management with confidence! 📚

平台分布

Claude Code

32.34%
按下载量换算107

windsurf

22.16%
按下载量换算73

OpenCode

18.51%
按下载量换算61

Codex

12.31%
按下载量换算41

Antigravity

7.67%
按下载量换算25

Gemini CLI

3.41%
按下载量换算11

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。

继续浏览同类 Skills