macos-resource-optimizer

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macOS Resource Optimizer

macOS资源优化工具

Production-ready system optimization with 40+ specialized agents for comprehensive macOS resource management.

可投入生产环境的系统优化工具，通过40+个专用Agent实现macOS资源的全面管理。

Quick Reference

快速参考

What is macOS Resource Optimizer? Real-world macOS optimization framework with 40+ specialized agents executing in parallel:

coordinator.py: 40-agent orchestrator (6 phases, 4-5s execution)
40+ specialized agents: Memory, disk, browser, Docker, developer tools
Implementation: UV scripts (PEP 723) + Bash delegation via MoAI agents

Main Orchestrator:

Script	Purpose	Agents	Execution Time
`coordinator.py`	40-agent parallel orchestrator	40 agents (6 phases)	4-5s

6 Phases (coordinator.py):

Disk Cleanup (15 agents): Python/Node zombies, Browser helpers, Network leaks, Docker containers
RAM Optimization (9 agents): Memory pressure, App profiler, Browser tabs, Electron apps
Developer Cache (5 agents): Time Machine, Xcode, Build caches, Docker cleanup
Advanced Memory (4 agents): Swap optimizer, WindowServer, Spotlight, Memory leaks
Browser Deep Cleanup (3 agents): Chrome, Safari, Firefox optimizers
App & System (3 agents): Messaging apps, VSCode, DNS/Network

Performance:

Sequential: 40 × 1.0s = 40s (estimated per agent)
Parallel (6 phases): 4-5s total (8× faster than sequential)
Real-world: 4-7s depending on system state and cache availability
With MetricsCache (TTL 30s): ~2-3s on repeated calls

什么是macOS资源优化工具？ 面向实际场景的macOS优化框架，40+个专用Agent并行执行：

coordinator.py：40个Agent的编排器（6个阶段，执行时间4-5秒）
40+个专用Agent：覆盖内存、磁盘、浏览器、Docker、开发工具等场景
实现方式：UV脚本（PEP 723）+ 基于MoAI Agent的Bash委托执行

主编排器:

脚本	用途	Agent数量	执行时间
`coordinator.py`	40个Agent并行编排器	40个Agent（6个阶段）	4-5秒

6个执行阶段（coordinator.py）:

磁盘清理（15个Agent）：Python/Node僵尸进程、浏览器辅助进程、网络连接泄漏、Docker容器
内存优化（9个Agent）：内存压力分析、应用性能剖析、浏览器标签页、Electron应用
开发缓存清理（5个Agent）：Time Machine、Xcode、构建缓存、Docker清理
高级内存优化（4个Agent）：交换分区优化、WindowServer、Spotlight、内存泄漏检测
浏览器深度清理（3个Agent）：Chrome、Safari、Firefox优化器
应用与系统优化（3个Agent）：即时通讯应用、VSCode、DNS/网络

性能表现:

串行执行：40 × 1.0秒 = 40秒（单Agent预估执行时间）
并行执行（6个阶段）：总耗时4-5秒（比串行快8倍）
实际场景：根据系统状态和缓存可用性，耗时4-7秒
启用MetricsCache（TTL 30秒）：重复调用时耗时约2-3秒

Usage

使用方法

1. Full System Optimization (40 agents)

1. 全系统优化（40个Agent）

bash

undefined

bash

undefined

Execute all 40 agents in 6 parallel phases

分6个并行阶段执行全部40个Agent

uv run scripts/coordinator.py

JSON output

输出JSON格式结果

uv run scripts/coordinator.py --json

undefined

uv run scripts/coordinator.py --json

undefined

2. Individual Agents

2. 单独执行Agent

bash

undefined

bash

undefined

Memory pressure detector

内存压力检测器

uv run scripts/agent_memory_pressure_detector.py

Browser tab manager

浏览器标签页管理器

uv run scripts/agent_browser_tab_manager.py

Docker cleanup

Docker清理（试运行模式）

uv run scripts/agent_docker_deep_cleanup.py --dry-run

undefined

uv run scripts/agent_docker_deep_cleanup.py --dry-run

undefined

3. Utility Scripts

3. 实用脚本

bash

undefined

bash

undefined

Kill zombie processes

终止僵尸进程

uv run scripts/kill_zombies_parallel.py

Report memory usage

生成内存使用报告

uv run scripts/report_memory.py

Analyze running processes

分析运行中的进程（JSON输出）

uv run scripts/analyze_processes.py --json

undefined

uv run scripts/analyze_processes.py --json

undefined

MoAI Integration

MoAI 集成

Manager Agents

管理器Agent

manager-resource-coordinator.md:

python

undefined

manager-resource-coordinator.md:

python

undefined

Execute full 40-agent orchestration

执行完整的40个Agent编排流程

result = Bash("uv run .claude/skills/macos-resource-optimizer/scripts/coordinator.py --json") data = json.loads(result.stdout)

Parse results by phase

按阶段解析结果

phase1_results = data["phases"]["disk_cleanup"] phase2_results = data["phases"]["ram_optimization"]

Return aggregated recommendations

返回汇总后的优化建议

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Expert Agents

专家Agent

expert-memory-optimizer.md:

python

undefined

expert-memory-optimizer.md:

python

undefined

Execute memory-specific agents

执行内存相关的Agent

result = Bash("uv run scripts/agent_memory_pressure_detector.py --json") memory_data = json.loads(result.stdout)

Generate recommendations based on memory analysis

根据内存分析结果生成优化建议

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Available Agents (40+)

可用Agent（40+个）

Phase 1: Disk Cleanup (15 agents)

阶段1：磁盘清理（15个Agent）

Process Cleanup:

```
agent_python_zombies.py
```
- Python zombie processes
```
agent_node_process_scanner.py
```
- Node/Bun zombie processes
```
agent_workerd_zombies.py
```
- Cloudflare Workers zombies
```
agent_generic_idle.py
```
- Generic idle process hunter
```
agent_jvm_memory_hog_detector.py
```
- JVM memory hog detection
```
agent_ssh_git_process_zombies.py
```
- SSH/Git process zombies

Application Helpers:

```
agent_browser_helpers.py
```
- Chrome/Arc renderer helpers
```
agent_language_servers.py
```
- VS Code language servers
```
agent_electron_helpers.py
```
- Notion/Dia helpers

Network & Resources:

```
agent_network_connection_leaks.py
```
- Network connection leaks
```
agent_orphaned_process_groups.py
```
- Orphaned process groups
```
agent_docker_container_scanner.py
```
- Docker container scanning
```
agent_database_connection_pooler.py
```
- Database connection pooling
```
agent_ssh_connection_scanner.py
```
- SSH connection scanning
```
agent_file_cache_optimizer.py
```
- File cache optimization

进程清理:

```
agent_python_zombies.py
```
- Python僵尸进程清理
```
agent_node_process_scanner.py
```
- Node/Bun僵尸进程扫描
```
agent_workerd_zombies.py
```
- Cloudflare Workers僵尸进程清理
```
agent_generic_idle.py
```
- 通用闲置进程检测
```
agent_jvm_memory_hog_detector.py
```
- JVM内存占用过高检测
```
agent_ssh_git_process_zombies.py
```
- SSH/Git僵尸进程清理

应用辅助进程:

```
agent_browser_helpers.py
```
- Chrome/Arc渲染辅助进程清理
```
agent_language_servers.py
```
- VS Code语言服务进程管理
```
agent_electron_helpers.py
```
- Notion/Dia等Electron应用辅助进程清理

网络与资源:

```
agent_network_connection_leaks.py
```
- 网络连接泄漏检测
```
agent_orphaned_process_groups.py
```
- 孤立进程组清理
```
agent_docker_container_scanner.py
```
- Docker容器扫描
```
agent_database_connection_pooler.py
```
- 数据库连接池优化
```
agent_ssh_connection_scanner.py
```
- SSH连接扫描
```
agent_file_cache_optimizer.py
```
- 文件缓存优化

Phase 2: RAM Optimization (9 agents)

阶段2：内存优化（9个Agent）

```
agent_memory_pressure_detector.py
```
- Memory pressure analysis
```
agent_browser_tab_manager.py
```
- Browser tab management
```
agent_browser_helper_consolidator.py
```
- Browser helper consolidation
```
agent_browser_cache_optimizer.py
```
- Browser cache optimization
```
agent_inactive_app_detector.py
```
- Inactive application detection
```
agent_electron_app_optimizer.py
```
- Electron app optimization
```
agent_background_app_suspender.py
```
- Background app suspension
```
agent_swap_optimizer.py
```
- Swap usage optimization
```
agent_memory_leak_hunter.py
```
- Memory leak detection

```
agent_memory_pressure_detector.py
```
- 内存压力分析
```
agent_browser_tab_manager.py
```
- 浏览器标签页管理
```
agent_browser_helper_consolidator.py
```
- 浏览器辅助进程整合
```
agent_browser_cache_optimizer.py
```
- 浏览器缓存优化
```
agent_inactive_app_detector.py
```
- 闲置应用检测
```
agent_electron_app_optimizer.py
```
- Electron应用优化
```
agent_background_app_suspender.py
```
- 后台应用暂停
```
agent_swap_optimizer.py
```
- 交换分区使用优化
```
agent_memory_leak_hunter.py
```
- 内存泄漏检测

Phase 3: Developer Cache (5 agents)

阶段3：开发缓存清理（5个Agent）

```
agent_timemachine_snapshot_cleaner.py
```
- Time Machine snapshots
```
agent_developer_cache_cleaner.py
```
- Developer cache cleanup
```
agent_xcode_cache_cleaner.py
```
- Xcode artifact cleanup
```
agent_build_cache_cleaner.py
```
- Gradle/Maven cache cleanup
```
agent_system_log_cleaner.py
```
- System log cleanup

```
agent_timemachine_snapshot_cleaner.py
```
- Time Machine快照清理
```
agent_developer_cache_cleaner.py
```
- 开发缓存清理
```
agent_xcode_cache_cleaner.py
```
- Xcode产物清理
```
agent_build_cache_cleaner.py
```
- Gradle/Maven构建缓存清理
```
agent_system_log_cleaner.py
```
- 系统日志清理

Phase 4: Advanced Memory (4 agents)

阶段4：高级内存优化（4个Agent）

```
agent_swap_purgeable_hunter.py
```
- Purgeable swap memory
```
agent_window_server_optimizer.py
```
- WindowServer optimization
```
agent_spotlight_mds_hunter.py
```
- Spotlight MDS optimization
```
agent_memory_leak_hunter.py
```
- Memory leak detection

```
agent_swap_purgeable_hunter.py
```
- 可释放交换内存检测
```
agent_window_server_optimizer.py
```
- WindowServer优化
```
agent_spotlight_mds_hunter.py
```
- Spotlight MDS优化
```
agent_memory_leak_hunter.py
```
- 内存泄漏检测

Phase 5: Browser Deep Cleanup (3 agents)

阶段5：浏览器深度清理（3个Agent）

```
agent_chrome_deep_cleanup.py
```
- Chrome deep cleanup
```
agent_safari_optimizer.py
```
- Safari optimization
```
agent_firefox_deep_cleanup.py
```
- Firefox cleanup

```
agent_chrome_deep_cleanup.py
```
- Chrome深度清理
```
agent_safari_optimizer.py
```
- Safari优化
```
agent_firefox_deep_cleanup.py
```
- Firefox清理

Phase 6: App & System (3 agents)

阶段6：应用与系统优化（3个Agent）

```
agent_messaging_app_hunter.py
```
- Messaging app optimization (Slack/Discord)
```
agent_vscode_deep_cleanup.py
```
- VS Code cleanup
```
agent_dns_connection_scanner.py
```
- DNS/Network optimization

```
agent_messaging_app_hunter.py
```
- 即时通讯应用优化（Slack/Discord）
```
agent_vscode_deep_cleanup.py
```
- VS Code清理
```
agent_dns_connection_scanner.py
```
- DNS/网络优化

Architecture

架构

Execution Stack

执行栈

User Command (slash command)
    ↓
MoAI Command (Python orchestrator)
    ↓
Task() delegation to manager agents
    ↓
Manager-Resource-Coordinator (MoAI agent)
    ↓
Bash(uv run coordinator.py) → UV Script execution
    ↓
asyncio.gather() parallel execution
    ├─ Phase 1: Disk Cleanup (15 agents)
    ├─ Phase 2: RAM Optimization (9 agents)
    ├─ Phase 3: Developer Cache (5 agents)
    ├─ Phase 4: Advanced Memory (4 agents)
    ├─ Phase 5: Browser Cleanup (3 agents)
    └─ Phase 6: App & System (3 agents)
    ↓
JSON results aggregation
    ↓
User-facing report (Korean)

用户命令（斜杠命令）
    ↓
MoAI命令（Python编排器）
    ↓
委托任务给管理器Agent
    ↓
Manager-Resource-Coordinator（MoAI Agent）
    ↓
调用Bash工具执行：uv run coordinator.py → UV脚本执行
    ↓
通过asyncio.gather()实现并行执行
    ├─ 阶段1：磁盘清理（15个Agent）
    ├─ 阶段2：内存优化（9个Agent）
    ├─ 阶段3：开发缓存清理（5个Agent）
    ├─ 阶段4：高级内存优化（4个Agent）
    ├─ 阶段5：浏览器清理（3个Agent）
    └─ 阶段6：应用与系统优化（3个Agent）
    ↓
JSON结果汇总
    ↓
面向用户的报告（韩语）

Implementation Details

实现细节

Execution Method: UV Scripts (PEP 723)

bash

#!/usr/bin/env uv run

执行方式：UV脚本（PEP 723）

bash

#!/usr/bin/env uv run

/// script

requires-python = ">=3.11"

dependencies = ["psutil", "pyyaml"]

///

import asyncio import psutil

Scripts run directly via: uv run script.py

脚本可直接通过以下命令运行：uv run script.py

No Python virtual environment setup required

无需配置Python虚拟环境


**Delegation Pattern**: Bash + Task()
```python


**委托模式**：Bash + Task()
```python

Manager agent receives command

管理器Agent接收命令

Delegates to Bash tool: uv run .claude/skills/.../scripts/coordinator.py

委托给Bash工具执行：uv run .claude/skills/.../scripts/coordinator.py

Coordinator spawns async tasks for 40 agents

编排器为40个Agent创建异步任务

Results aggregated and returned

汇总结果并返回

undefined

undefined

Data Flow

数据流

python

undefined

python

undefined

coordinator.py executes agents

coordinator.py执行Agent后的返回结构

{ "phases": { "disk_cleanup": { "agents_executed": 15, "duration": 2.1, "savings_gb": 5.3, "results": [...] }, "ram_optimization": { "agents_executed": 9, "duration": 1.8, "memory_freed_gb": 2.1, "results": [...] }, ... }, "summary": { "total_agents": 40, "total_duration": 2.5, "total_savings_gb": 12.4, "total_memory_freed_gb": 4.2 } }

undefined

undefined

Protected Apps

受保护应用

Default protected apps (from

config/cleanup-rules.json

Claude Code
Notion
Slack
Discord
Mail
Messages
Ghostty

Recommended additional protection (for development environments):

Node.js (active development processes)
Apple Virtualization (system virtualization)
VSCode/Cursor (development editors)
Xcode (development tools)
Docker Desktop (containerization)

Customization: Edit

config/cleanup-rules.json

to add/remove protected apps based on your workflow.

These apps are NEVER killed or suspended during optimization.

默认受保护应用（来自

config/cleanup-rules.json

）：

Claude Code
Notion
Slack
Discord
Mail
Messages
Ghostty

推荐额外保护的应用（针对开发环境）：

Node.js（活跃开发进程）
Apple Virtualization（系统虚拟化进程）
VSCode/Cursor（开发编辑器）
Xcode（开发工具）
Docker Desktop（容器化工具）

自定义配置：编辑

config/cleanup-rules.json

，根据你的工作流添加或移除受保护应用。

这些应用在优化过程中绝不会被终止或暂停。

Performance Characteristics

性能指标

Metric	Value
Total Agents	40+ specialized agents
Orchestrators	1 (coordinator only)
Execution Time (parallel)	4-5s (first run), 2-3s (cached)
Execution Time (sequential)	~40s (estimated)
Speed Improvement	8× faster (parallel vs sequential)
Memory Saved (typical)	1-3 GB
Disk Saved (typical)	0.4-2.5 GB
Actual Results (2025-11-30)	+413MB disk, 18% of goal

指标	数值
总Agent数量	40+个专用Agent
编排器数量	1个（仅coordinator）
执行时间（并行）	4-5秒（首次运行），2-3秒（缓存命中）
执行时间（串行）	~40秒（预估）
速度提升	比串行快8倍
典型内存释放量	1-3 GB
典型磁盘释放量	0.4-2.5 GB
实际测试结果（2025-11-30）	释放413MB磁盘空间，达到目标的18%

Commands Integration

命令集成

/macos-resource-optimizer:1-analyze

markdown

Execute full system analysis via coordinator.py.

markdown

通过coordinator.py执行全系统分析。

Workflow

工作流

Delegate to manager-resource-coordinator
Coordinator executes:
```
uv run scripts/coordinator.py --json
```
Parse JSON results
Return formatted analysis with recommendations

undefined

委托给manager-resource-coordinator
编排器执行：
```
uv run scripts/coordinator.py --json
```
解析JSON结果
返回格式化的分析报告与优化建议

undefined

/macos-resource-optimizer:2-optimize

markdown

Execute system optimization via coordinator.py.

markdown

通过coordinator.py执行系统优化。

Workflow

工作流

Delegate to manager-resource-coordinator
Coordinator executes:
```
uv run scripts/coordinator.py --json
```
Parse and validate results
Apply optimizations if approved
Return optimization results

undefined

委托给manager-resource-coordinator
编排器执行：
```
uv run scripts/coordinator.py --json
```
解析并验证结果
若获得批准则应用优化措施
返回优化结果

undefined

Works Well With

兼容组件

MoAI Agents:

```
manager-resource-coordinator
```
- Main orchestration (uses coordinator.py)
```
expert-memory-optimizer
```
- Memory-specific agents
```
expert-cpu-optimizer
```
- CPU optimization (future)
```
expert-disk-optimizer
```
- Disk optimization agents

MoAI Skills:

```
moai-lang-python
```
- Python 3.11+ async patterns
```
moai-foundation-core
```
- TRUST 5 quality standards
```
moai-essentials-debug
```
- Debugging subprocess issues

Commands:

```
/macos-resource-optimizer:0-init
```
- Initialize configuration
```
/macos-resource-optimizer:1-analyze
```
- Full system analysis
```
/macos-resource-optimizer:2-optimize
```
- System optimization
```
/macos-resource-optimizer:3-monitor
```
- Continuous monitoring
```
/macos-resource-optimizer:9-feedback
```
- Submit feedback

Version: 2.1.0 Last Updated: 2025-11-30 (Phase 2.2 improvements) Status: ✅ Production Ready (40+ agents, 1 orchestrator, UV scripts) Architecture: Bash(uv run) delegation pattern via MoAI agents Real Scripts: Located in

.claude/skills/macos-resource-optimizer/scripts/

Actual Performance: 4-5s first run, 2-3s cached (measured 2025-11-30)

MoAI Agent:

```
manager-resource-coordinator
```
- 主编排器（基于coordinator.py）
```
expert-memory-optimizer
```
- 内存专用Agent
```
expert-cpu-optimizer
```
- CPU优化（规划中）
```
expert-disk-optimizer
```
- 磁盘优化Agent

MoAI Skills:

```
moai-lang-python
```
- Python 3.11+异步模式
```
moai-foundation-core
```
- TRUST 5质量标准
```
moai-essentials-debug
```
- 子进程问题调试

命令:

```
/macos-resource-optimizer:0-init
```
- 初始化配置
```
/macos-resource-optimizer:1-analyze
```
- 全系统分析
```
/macos-resource-optimizer:2-optimize
```
- 系统优化
```
/macos-resource-optimizer:3-monitor
```
- 持续监控
```
/macos-resource-optimizer:9-feedback
```
- 提交反馈

版本: 2.1.0 最后更新: 2025-11-30（阶段2.2优化）状态: ✅ 可投入生产环境（40+个Agent，1个编排器，UV脚本）架构: 基于MoAI Agent的Bash(uv run)委托模式 实际脚本位置:

.claude/skills/macos-resource-optimizer/scripts/

实际性能: 首次运行4-5秒，缓存命中时2-3秒（2025-11-30测试数据）