Ai File Organizer

AI 智能文件整理 - 批量重命名、自动分类、智能归档（异步引擎 + 云同步）

Security Scan

The skill largely matches a file-organizer's functionality, but there are inconsistencies in its metadata and clear privacy/credential risks (AI analysis + cloud sync that can transmit file contents) that you should review before installing or giving credentials.

Purpose & Capability

The skill's name/description (file organizer with AI analysis and cloud sync) aligns with the included code and docs. However the published registry 'Requirements' block said no required environment variables, while _meta.json and documentation list ALIYUN_ACCESS_KEY, ALIYUN_SECRET_KEY and BAIDU_ACCESS_TOKEN and network endpoints — an inconsistency in declared requirements. Requesting cloud provider credentials is coherent with cloud-sync features, but the mismatch between declared/required env vars is unexplained and worth questioning.

Instruction Scope

SKILL.md and the code instruct the agent/user to scan user directories, compute file hashes, persist caches under the user's home (~/.ai-organizer), and (optionally) send file contents/metadata to external services for AI analysis and upload to cloud providers. Sending file contents to an external LLM/service (dashscope) and to cloud endpoints is functionally expected for 'AI content analysis' and 'cloud sync', but it is a high privacy surface: these instructions permit reading arbitrary user files in user directories and transmitting their contents to external endpoints if AI or cloud sync is enabled. The documentation also claims 'sensitive path exclusion' and 'encrypted storage' — you should verify those are actually enforced in the code.

Install Mechanism

There is no formal install spec in the registry (instruction-only install). The Quickstart suggests pip installing dependencies (aiofiles, aiomultiprocess, tqdm, pyyaml and optionally dashscope). This is standard for a Python tool and less risky than arbitrary binary downloads. Still: installing third-party packages (especially less-known ones like 'dashscope') carries the usual supply-chain risk — inspect those packages before installing.

Credentials

The feature set justifies cloud credentials (ALIYUN_*, BAIDU_* and OneDrive equivalents) and possibly an API key for an LLM provider; those appear in README/_meta.json. However the top-level registry summary claimed 'Required env vars: none' while _meta.json lists environmentVariables. Also network access and endpoints (dashscope.aliyuncs.com, api.aliyundrive.com, pan.baidu.com) are declared in metadata: granting credentials and network access would allow uploading user files and sending content to external LLMs. Require only the credentials you intend to use, and avoid entering secrets unless you trust the code and host.

Persistence & Privilege

The skill persists state to the user's home (~/.ai-organizer) (cache file, logs), writes to user-specified target folders and creates version folders. always: false (not force-enabled). Persistence is expected for this tool, but review and control where data is stored, and ensure the 'sensitive path exclusion' logic works before running broadly or with cloud sync enabled.

What to consider before installing

This skill appears to implement the advertised file-organization features, including optional AI analysis and cloud-sync which will read user files and may transmit their contents to external services. Before installing or providing any credentials: 1) Verify the skill source/trustworthiness (the package homepage/source is missing). 2) Review scripts/organizer.py (particularly network calls and any code that uploads or posts file content) or run it in a sandboxed account. 3) If you need only local features, keep ai_analysis and cloud_sync disabled and do not set cloud/LLM credentials. 4) If you enable cloud sync or AI analysis, create and scope credentials with least privilege and prefer temporary/test accounts. 5) Confirm that 'sensitive path exclusion' and config encryption are actually implemented (search code for exclusion patterns and encryption calls). 6) Inspect and vet third-party dependencies (e.g., 'dashscope') before pip installing. If you want, I can scan organizer.py for specific network calls and the exact places file contents are transmitted and summarize those lines for you.

AI File Organizer Skill v3.0.0

下一代智能文件整理工具 - 异步引擎、AI 内容分析、云同步、版本管理

🎯 触发条件

• 手动触发: /organize-files 或 "帮我整理文件"、"清理重复文件"
• 定时触发: 每周/每月自动整理下载文件夹
• 文件夹监控: 监控指定文件夹自动整理
• 云同步触发: 文件整理完成后自动同步到云端

✨ 核心功能

1. 异步处理引擎 🚀

• 并发处理: 基于 asyncio 的异步 IO，速度提升 40%
• 智能调度: 自动优化并发数，适配不同硬件
• 进度追踪: 实时进度条 + 预估完成时间
• 错误隔离: 单文件失败不影响整体流程

2. AI 内容分析 🧠

• 智能标签: LLM 分析文件内容，生成精准描述
• 语义分类: 基于内容语义自动分类，非简单关键词匹配
• 置信度评分: 每个分类附带置信度，低置信度可人工复核
• 自学习: 根据用户反馈优化分类模型

3. 智能缓存系统 💾

• 哈希缓存: 文件哈希缓存，避免重复计算
• 分类缓存: 已分类结果缓存，二次整理速度提升 70%
• TTL 管理: 自动过期机制，缓存不过度占用空间
• 持久化: 重启后缓存依然有效

4. 云同步支持 ☁️

• 多云支持: 阿里云盘、百度网盘、OneDrive
• 自动同步: 整理完成后自动上传到云端
• 增量同步: 仅上传变更文件，节省带宽
• 断点续传: 网络中断后可继续传输

5. 文件版本管理 🔄

• 自动版本: 文件变更自动保留历史版本
• 版本对比: 支持查看不同版本差异
• 一键恢复: 快速恢复到任意历史版本
• 版本清理: 自动清理过期版本，节省空间

6. 重复文件清理 🗑️

• 内容哈希: SHA256 哈希检测完全重复
• 相似度检测: 感知哈希检测相似图片
• 智能保留: 自动保留最佳版本（最高质量/最早创建）
• 安全删除: 移动到回收站而非直接删除

7. 交互式 CLI 👆

• 预览模式: 操作前预览整理方案
• 交互确认: 关键操作前请求确认
• 详细日志: 结构化日志，支持 JSON 导出
• 丰富输出: Emoji、进度条、彩色输出

8. 智能清理建议 💡

• 临时文件: 识别并建议删除系统临时文件
• 缓存清理: 应用缓存、浏览器缓存清理建议
• 大文件检测: 找出占用空间的大文件
• 重复下载: 检测重复下载的文件

📋 配置参数

# 命名规则
naming:
  format: "{date}_{type}_{original}"  # 日期_类型_原名
  date_format: "%Y%m%d"
  max_length: 100
  replace_spaces: true

# 分类规则
classification:
  enabled: true
  ai_analysis: true  # 启用 AI 内容分析
  categories:
    - name: "工作文档"
      keywords: ["报告", "方案", "合同", "发票"]
      folder: "Work/Documents"
    - name: "学习资料"
      keywords: ["教程", "课程", "笔记"]
      folder: "Learning"
    - name: "图片视频"
      extensions: ["jpg", "png", "mp4", "mov"]
      folder: "Media"
    - name: "代码项目"
      extensions: ["py", "js", "java", "go", "rs"]
      folder: "Code"

# 重复文件处理
duplicates:
  enabled: true
  similarity_threshold: 0.95
  keep_best: true
  move_to_folder: "_duplicates"

# 云同步
cloud_sync:
  enabled: false
  provider: "aliyun"  # aliyun | baidu | onedrive
  access_key: "${ALIYUN_ACCESS_KEY}"
  secret_key: "${ALIYUN_SECRET_KEY}"
  bucket: "my-files"
  auto_sync: true

# 版本管理
versioning:
  enabled: true
  max_versions: 5
  version_folder: ".versions"

# 缓存
cache:
  enabled: true
  max_size: 10000
  ttl_days: 7

# 性能
performance:
  max_concurrent: 10
  chunk_size: 8192
  use_async_io: true

# 日志
logging:
  level: "INFO"
  file: "logs/organizer.log"
  format: "json"

🚀 使用示例

示例 1: 整理下载文件夹

# 基础整理
python scripts/organizer.py --organize ~/Downloads

# 指定目标文件夹
python scripts/organizer.py --organize ~/Downloads --target ~/Organized

# 高性能模式
python scripts/organizer.py --organize ~/Downloads --concurrent 20

示例 2: 清理重复文件

# 检测重复
python scripts/organizer.py --duplicates ~/Files

# 清理并移动
python scripts/organizer.py --duplicates ~/Files --move-to _duplicates

示例 3: 使用配置文件

# 使用自定义配置
python scripts/organizer.py --organize ~/Downloads --config config.yaml

# 导出整理报告
python scripts/organizer.py --organize ~/Downloads --report report.json

示例 4: 预览模式

# 先预览整理方案
python scripts/organizer.py --organize ~/Downloads --dry-run

# 交互确认模式
python scripts/organizer.py --organize ~/Downloads --interactive

示例 5: 云同步

# 配置环境变量
export ALIYUN_ACCESS_KEY="your_key"
export ALIYUN_SECRET_KEY="your_secret"

# 整理并同步
python scripts/organizer.py --organize ~/Downloads --config cloud_config.yaml

📊 输出示例

============================================================
🚀 开始文件整理 (v3.0.0 异步引擎)
============================================================
📂 源目录：/home/user/Downloads
📁 目标目录：/home/user/Organized
📊 发现 523 个文件

处理进度: 100%|████████████████| 523/523 [00:26<00:00, 20.1file/s]

============================================================
📊 整理完成
============================================================
总文件数：523
✅ 成功：520
❌ 失败：3
⚡ 速度：20.0 个/秒
⏱️  耗时：26.0 秒
💾 缓存命中率：68.5%

分类统计:
  📄 Documents: 125 个
  🖼️  Images: 234 个
  🎥  Videos: 89 个
  💻  Code: 45 个
  📦  Archives: 27 个

📋 报告已导出：report.json

🔧 命令行参数

usage: organizer.py [-h] [--demo] [--organize DIR] [--target DIR]
                    [--duplicates DIR] [--config FILE] [--concurrent N]
                    [--no-cache] [--verbose] [--report FILE]

可选参数:
  -h, --help            显示帮助信息
  --demo                运行演示
  --organize DIR        整理指定文件夹
  --target DIR          目标文件夹
  --duplicates DIR      检测重复文件
  --config FILE         配置文件路径
  --concurrent N        最大并发数 (默认：10)
  --no-cache            禁用缓存
  --verbose, -v         详细输出
  --report FILE         导出报告路径

📈 性能基准

场景	v2.0.0	v3.0.0	提升
1000 文件	45 秒	26 秒	73% ⬆️
10000 文件	8 分钟	4.5 分钟	78% ⬆️
内存占用	256MB	128MB	50% ⬇️
缓存命中率	0%	70%	新增

🛡️ 安全特性

• 只读优先: 默认复制而非移动，原文件保留
• 操作审计: 完整记录所有操作日志
• 权限检查: 自动检查文件访问权限
• 敏感路径排除: 自动跳过系统目录和隐藏目录
• 还原点: 操作前自动创建还原点
• 加密存储: 配置文件中的敏感信息加密存储

🔌 扩展开发

添加自定义分类器

from organizer import AIFileOrganizer

class CustomOrganizer(AIFileOrganizer):
    def classify_file(self, file_path, filename):
        # 自定义分类逻辑
        if 'invoice' in filename.lower():
            return 'Finance/Invoices', 0.95
        return super().classify_file(file_path, filename)

添加云存储 provider

from cloud_providers.base import BaseCloudProvider

class CustomCloudProvider(BaseCloudProvider):
    def upload(self, file_path, remote_path):
        # 实现上传逻辑
        pass
    
    def download(self, remote_path, local_path):
        # 实现下载逻辑
        pass

🐛 常见问题

Q: 处理速度慢？

A:

1. 增加并发数：--concurrent 20
2. 启用缓存：确保 cache.enabled: true
3. 检查磁盘 IO 性能

Q: 分类不准确？

A:

1. 完善分类规则的关键词
2. 启用 AI 内容分析：ai_analysis.enabled: true
3. 检查文件名是否包含足够信息

Q: 云同步失败？

A:

1. 检查 API 密钥配置
2. 确认网络连接正常
3. 查看日志：logs/organizer.log

📚 相关文档

• README.md - 完整文档
• QUICKSTART.md - 快速开始
• CHANGELOG.md - 更新日志
• docs/PERFORMANCE.md - 性能调优

🧪 测试

# 单元测试
python -m pytest tests/test_organizer.py -v

# 覆盖率报告
python -m pytest tests/test_organizer.py -v --cov=scripts --cov-report=html

# 性能基准测试
python tests/benchmark.py

📦 依赖

必需:

• Python 3.8+
• aiofiles
• aiomultiprocess

可选:

• tqdm (进度条)
• pyyaml (YAML 配置)
• dashscope (AI 内容分析)

📄 许可证

MIT License

👥 作者

于金泽

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版本: 3.0.0
更新日期: 2026-03-16
文档: https://github.com/your-repo/ai-file-organizer