القائمة
macOS system resource optimization with 40 specialized agents for memory, disk, CPU, and process management
يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.
اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
يتجاوز الأمر المباشر Prompt المخصّص للمراجعة. افحص المصدر قبل تشغيله.
npx skills add https://github.com/rdmptv/AdbAutoPlayer --skill macos-resource-optimizerيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
تفضّل نسخة محلية؟ نزّل الملفات المتاحة حاليًا لدى SkillsMP.
عرض SKILL.md
| name | macos-resource-optimizer |
| description | macOS system resource optimization with 40 specialized agents for memory, disk, CPU, and process management |
| version | 2.1.0 |
| scripts_enabled | true |
| last_updated | "2025-11-30T00:00:00.000Z" |
| updated_in_phase | 2.2 |
| improvements | Performance metrics corrected, UV script architecture documented, protected apps expanded |
| auto_trigger_keywords | ["macos","memory","optimizer","performance","ram","disk","cleanup","resource"] |
| scripts | [{"name":"coordinator","path":"scripts/coordinator.py","description":"Main orchestrator spawning 40 agents concurrently across 6 phases"}] |
| color | blue |
Production-ready system optimization with 40+ specialized agents for comprehensive macOS resource management.
What is macOS Resource Optimizer? Real-world macOS optimization framework with 40+ specialized agents executing in parallel:
Main Orchestrator:
| Script | Purpose | Agents | Execution Time |
|---|---|---|---|
coordinator.py | 40-agent parallel orchestrator | 40 agents (6 phases) | 4-5s |
6 Phases (coordinator.py):
Performance:
# Execute all 40 agents in 6 parallel phases
uv run scripts/coordinator.py
# JSON output
uv run scripts/coordinator.py --json
# Memory pressure detector
uv run scripts/agent_memory_pressure_detector.py
# Browser tab manager
uv run scripts/agent_browser_tab_manager.py
uv run scripts/agent_docker_deep_cleanup.py --dry-run
# Kill zombie processes
uv run scripts/kill_zombies_parallel.py
# Report memory usage
uv run scripts/report_memory.py
# Analyze running processes
uv run scripts/analyze_processes.py --json
manager-resource-coordinator.md:
# Execute full 40-agent orchestration
result = Bash("uv run .claude/skills/macos-resource-optimizer/scripts/coordinator.py --json")
data = json.loads(result.stdout)
# Parse results by phase
phase1_results = data["phases"]["disk_cleanup"]
phase2_results = data["phases"]["ram_optimization"]
# Return aggregated recommendations
expert-memory-optimizer.md:
# Execute memory-specific agents
result = Bash("uv run scripts/agent_memory_pressure_detector.py --json")
memory_data = json.loads(result.stdout)
# Generate recommendations based on memory analysis
Process Cleanup:
agent_python_zombies.py - Python zombie processesagent_node_process_scanner.py - Node/Bun zombie processesagent_workerd_zombies.py - Cloudflare Workers zombiesagent_generic_idle.py - Generic idle process hunteragent_jvm_memory_hog_detector.py - JVM memory hog detectionagent_ssh_git_process_zombies.py - SSH/Git process zombiesApplication Helpers:
agent_browser_helpers.py - Chrome/Arc renderer helpersagent_language_servers.py - VS Code language serversagent_electron_helpers.py - Notion/Dia helpersNetwork & Resources:
agent_network_connection_leaks.py - Network connection leaksagent_orphaned_process_groups.py - Orphaned process groupsagent_docker_container_scanner.py - Docker container scanningagent_database_connection_pooler.py - Database connection poolingagent_ssh_connection_scanner.py - SSH connection scanningagent_file_cache_optimizer.py - File cache optimizationagent_memory_pressure_detector.py - Memory pressure analysisagent_browser_tab_manager.py - Browser tab managementagent_browser_helper_consolidator.py - Browser helper consolidationagent_browser_cache_optimizer.py - Browser cache optimizationagent_inactive_app_detector.py - Inactive application detectionagent_electron_app_optimizer.py - Electron app optimizationagent_background_app_suspender.py - Background app suspensionagent_swap_optimizer.py - Swap usage optimizationagent_memory_leak_hunter.py - Memory leak detectionagent_timemachine_snapshot_cleaner.py - Time Machine snapshotsagent_developer_cache_cleaner.py - Developer cache cleanupagent_xcode_cache_cleaner.py - Xcode artifact cleanupagent_build_cache_cleaner.py - Gradle/Maven cache cleanupagent_system_log_cleaner.py - System log cleanupagent_swap_purgeable_hunter.py - Purgeable swap memoryagent_window_server_optimizer.py - WindowServer optimizationagent_spotlight_mds_hunter.py - Spotlight MDS optimizationagent_memory_leak_hunter.py - Memory leak detectionagent_chrome_deep_cleanup.py - Chrome deep cleanupagent_safari_optimizer.py - Safari optimizationagent_firefox_deep_cleanup.py - Firefox cleanupagent_messaging_app_hunter.py - Messaging app optimization (Slack/Discord)agent_vscode_deep_cleanup.py - VS Code cleanupagent_dns_connection_scanner.py - DNS/Network optimizationUser 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)
Execution Method: UV Scripts (PEP 723)
#!/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
# No Python virtual environment setup required
Delegation Pattern: Bash + Task()
# Manager agent receives command
# Delegates to Bash tool: uv run .claude/skills/.../scripts/coordinator.py
# Coordinator spawns async tasks for 40 agents
# Results aggregated and returned
# coordinator.py executes agents
{
"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
}
}
Default protected apps (from config/cleanup-rules.json):
Recommended additional protection (for development environments):
Customization: Edit config/cleanup-rules.json to add/remove protected apps based on your workflow.
These apps are NEVER killed or suspended during optimization.
| 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 |
Execute full system analysis via coordinator.py.
## Workflow
1. Delegate to manager-resource-coordinator
2. Coordinator executes: `uv run scripts/coordinator.py --json`
3. Parse JSON results
4. Return formatted analysis with recommendations
Execute system optimization via coordinator.py.
## Workflow
1. Delegate to manager-resource-coordinator
2. Coordinator executes: `uv run scripts/coordinator.py --json`
3. Parse and validate results
4. Apply optimizations if approved
5. Return optimization results
MoAI Agents:
manager-resource-coordinator - Main orchestration (uses coordinator.py)expert-memory-optimizer - Memory-specific agentsexpert-cpu-optimizer - CPU optimization (future)expert-disk-optimizer - Disk optimization agentsMoAI Skills:
moai-lang-python - Python 3.11+ async patternsmoai-foundation-core - TRUST 5 quality standardsmoai-essentials-debug - Debugging subprocess issuesCommands:
/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 feedbackVersion: 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)
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