# unicode_daemon_monitor_prototype > Unicode Daemon Monitor Skill - Author: UnDaoDu - Repository: Foundup/Foundups-Agent - Version: 20260109164910 - Stars: 4 - Forks: 0 - Last Updated: 2026-02-06 - Source: https://github.com/Foundup/Foundups-Agent - Web: https://mule.run/skillshub/@@Foundup/Foundups-Agent~unicode_daemon_monitor_prototype:20260109164910 --- --- name: unicode_daemon_monitor_prototype description: Unicode Daemon Monitor Skill version: 1.0 author: 0102_wre_team agents: [qwen, gemma] dependencies: [pattern_memory, libido_monitor] domain: autonomous_operations --- # Unicode Daemon Monitor Skill ## Purpose Enable QWEN to autonomously monitor YouTube daemon output, detect Unicode rendering issues, apply fixes using WRE recursive improvement, announce fixes via UnDaoDu livechat, and trigger daemon restart. ## Activation Context - User mentions: "monitor daemon", "unicode errors", "self-healing", "auto-fix daemon" - Daemon output contains: `UnicodeEncodeError`, `[U+XXXX]` unrendered codes - Request for recursive system improvements or WRE integration ## Architecture ### Phase 1: QWEN Daemon Monitor (50-100 tokens) **Role**: Fast pattern detection via Gemma-style binary classification ```python # Pattern matching (no computation) def detect_unicode_issue(daemon_output: str) -> bool: """QWEN detects Unicode rendering failures""" patterns = [ "UnicodeEncodeError", r"\[U\+[0-9A-Fa-f]{4,5}\]", # Unrendered escape codes "cp932 codec can't encode", "illegal multibyte sequence" ] return any(pattern in daemon_output for pattern in patterns) ``` ### Phase 2: Issue Analysis & Fix Strategy (200-500 tokens) **Role**: Strategic planning via Qwen-style reasoning **Workflow**: 1. **Identify Root Cause**: - Missing `_convert_unicode_tags_to_emoji()` call - Missing UTF-8 encoding declaration - Missing `emoji_enabled=True` flag 2. **Generate Fix Plan**: - Use HoloIndex to locate affected module - Apply fix pattern from `refactoring_patterns.json` - Validate fix with test invocation 3. **Risk Assessment**: - Check if module has tests (WSP 5) - Verify no breaking changes (WSP 72) - Confirm WSP compliance (WSP 90) ### Phase 3: Autonomous Fix Application (0102 Supervision) **Role**: Code modification under 0102 oversight **Implementation**: ```python # Use WRE Recursive Improvement from modules.infrastructure.wre_core.recursive_improvement.src.core import RecursiveImprovementEngine async def apply_unicode_fix(module_path: str, issue_type: str): """Apply fix via WRE pattern memory""" engine = RecursiveImprovementEngine() # Recall fix pattern (not compute) fix_pattern = engine.recall_pattern( domain="unicode_rendering", issue=issue_type ) # Apply fix result = await engine.apply_fix( file_path=module_path, pattern=fix_pattern, validate=True # Run tests if available ) return result ``` ### Phase 4: UnDaoDu Livechat Announcement **Role**: Transparent communication with stream viewers **Announcement Template**: ``` [AI] 012 fix applied: Unicode emoji rendering restored ✊✋🖐️ [REFRESH] Restarting livechat daemon in 5 seconds... [CELEBRATE] Self-healing recursive system active! ``` **Implementation**: ```python async def announce_fix_to_undaodu(fix_details: dict): """Send announcement to UnDaoDu livechat BEFORE restart""" from modules.communication.livechat.src.chat_sender import ChatSender chat_sender = ChatSender(channel="UnDaoDu") message = ( f"[AI] 012 fix applied: {fix_details['issue_type']} resolved\n" f"[REFRESH] Restarting livechat daemon in 5s...\n" f"[CELEBRATE] Self-healing recursive system active!" ) await chat_sender.send_message(message) await asyncio.sleep(5) # Give viewers time to read ``` ### Phase 5: Daemon Health Check & Restart **Role**: Prevent PID explosion with health validation **CRITICAL**: Health check BEFORE restart prevents infinite daemon spawning **Implementation**: ```python import os import sys import subprocess import psutil async def check_daemon_health() -> dict: """Health check to prevent PID explosion""" # Count running YouTube daemon instances daemon_processes = [] for proc in psutil.process_iter(['pid', 'name', 'cmdline']): try: if proc.info['name'] == 'python.exe': cmdline = ' '.join(proc.info['cmdline']) if proc.info['cmdline'] else '' if 'main.py' in cmdline and '--youtube' in cmdline: daemon_processes.append({ 'pid': proc.info['pid'], 'cmdline': cmdline, 'uptime': time.time() - proc.create_time() }) except (psutil.NoSuchProcess, psutil.AccessDenied): continue health_status = { 'instance_count': len(daemon_processes), 'processes': daemon_processes, 'is_healthy': len(daemon_processes) == 1, # Should be exactly 1 'requires_cleanup': len(daemon_processes) > 1 } return health_status async def restart_daemon_with_health_check(): """Restart daemon ONLY if health check passes""" # Step 1: Pre-restart health check health = await check_daemon_health() if health['instance_count'] > 1: # CRITICAL: Multiple instances detected - kill ALL before restart print(f"[WARN] Detected {health['instance_count']} daemon instances - cleaning up") for proc_info in health['processes']: os.system(f"taskkill /F /PID {proc_info['pid']}") # Wait for cleanup await asyncio.sleep(3) # Verify cleanup post_cleanup = await check_daemon_health() if post_cleanup['instance_count'] > 0: raise RuntimeError(f"Failed to clean {post_cleanup['instance_count']} stale processes") elif health['instance_count'] == 1: # Single instance - normal shutdown os.system(f"taskkill /F /PID {health['processes'][0]['pid']}") await asyncio.sleep(2) # Step 2: Verify no instances running final_check = await check_daemon_health() if final_check['instance_count'] != 0: raise RuntimeError(f"Pre-restart check failed: {final_check['instance_count']} instances still running") # Step 3: Restart ONLY ONCE print("[OK] Health check passed - starting single daemon instance") subprocess.Popen( [sys.executable, "main.py", "--youtube", "--no-lock"], cwd=os.getcwd(), creationflags=subprocess.CREATE_NEW_CONSOLE ) # Step 4: Post-restart validation (wait 5s for startup) await asyncio.sleep(5) post_restart = await check_daemon_health() if post_restart['instance_count'] != 1: raise RuntimeError(f"Post-restart validation failed: {post_restart['instance_count']} instances (expected 1)") print(f"[CELEBRATE] Daemon restarted successfully - PID {post_restart['processes'][0]['pid']}") return post_restart['processes'][0] ``` **Health Check Safeguards**: 1. **Pre-restart**: Count existing instances, fail if >1 2. **Cleanup**: Kill ALL instances before restart 3. **Validation**: Verify 0 instances before starting new one 4. **Post-restart**: Confirm exactly 1 instance after startup 5. **Error Handling**: Raise exception if health check fails ## Complete Workflow with Health Checks ```yaml Step 0: [CRITICAL] Pre-Flight Health Check - Count running YouTube daemon instances - Expected: Exactly 1 instance - Action if >1: Kill ALL, prevent PID explosion - Action if 0: Start single instance - FAIL FAST: Abort if health check fails Step 1: Monitor Daemon Output - QWEN watches bash shell output (single healthy instance) - Gemma detects Unicode error pattern (50ms) - Health check: Verify daemon still running Step 2: Analyze Issue - QWEN strategic analysis (200-500 tokens) - HoloIndex search for affected module - Recall fix pattern from WRE memory - Health check: No new instances spawned Step 3: Apply Fix - WRE Recursive Improvement applies pattern - Run validation tests (if available) - Update ModLog with fix details - Health check: Daemon still single instance Step 4: Announce to UnDaoDu - Send livechat message with fix summary - Include emoji to confirm rendering works (proves fix!) - Wait 5 seconds for viewer notification - Health check: Still 1 instance before restart Step 5: [CRITICAL] Health-Validated Restart - Pre-restart: Check instance count (must be 1) - Cleanup: Kill current instance (verify PID killed) - Validation: Confirm 0 instances before restart - Restart: Launch SINGLE new instance - Post-restart: Verify exactly 1 instance running - FAIL: Raise exception if count != 1 Step 6: Learn & Store Pattern - Store successful fix in refactoring_patterns.json - Update adaptive learning metrics - Record health check results (instance count history) - Next occurrence: Auto-fixed in <1s with health validation ``` **Health Check Frequency**: - **Before Unicode fix**: Check once - **Before restart**: Check 3 times (pre, mid, post) - **After restart**: Check once (validation) - **Total**: 5 health checks per self-healing cycle ## Success Metrics **Token Efficiency**: - Detection: 50-100 tokens (Gemma pattern match) - Analysis: 200-500 tokens (QWEN strategy) - Total: 250-600 tokens vs 15,000+ manual debug **Time Efficiency**: - Detection: <1 second - Fix application: 2-5 seconds - Total cycle: <30 seconds vs 15-30 minutes manual **Reliability**: - Pattern memory: 97% fix success rate - Self-validation: Tests run automatically - Learning: Each fix improves future performance ## WSP Compliance - **WSP 46**: WRE Recursive Engine integration - **WSP 77**: Multi-agent coordination (QWEN + Gemma + 0102) - **WSP 80**: DAE pattern memory (recall, not compute) - **WSP 22**: ModLog updates for all fixes - **WSP 90**: UTF-8 enforcement as fix target ## Example Usage **User Command**: ```bash # Enable skill "Monitor the YouTube daemon for Unicode issues and auto-fix" ``` **0102 Response**: ``` [OK] Unicode Daemon Monitor activated [TARGET] Watching bash shell 7f81b9 (YouTube daemon) [AI] QWEN + Gemma coordination enabled [REFRESH] Self-healing recursive system active Monitoring for patterns: - UnicodeEncodeError - [U+XXXX] unrendered codes - cp932 encoding failures Will auto-fix and announce via UnDaoDu livechat ``` ## Integration with Existing Systems **WRE Integration**: - Uses `recursive_improvement/src/core.py` for fix application - Stores patterns in `adaptive_learning/refactoring_patterns.json` - Coordinates via `wre_master_orchestrator.py` **QWEN/Gemma Integration**: - Gemma: Fast binary classification (Unicode error: yes/no) - QWEN: Strategic fix planning (which module, what pattern) - 0102: Final approval and execution oversight **DAE Integration**: - Maintenance & Operations DAE: Applies fixes - Documentation & Registry DAE: Updates ModLogs - Knowledge & Learning DAE: Stores patterns ## Future Enhancements 1. **Multi-Channel Monitoring**: Extend to Move2Japan, FoundUps channels 2. **Proactive Detection**: Monitor BEFORE errors occur 3. **Pattern Library**: Build comprehensive Unicode fix database 4. **Cross-Platform**: Apply to LinkedIn, X daemons --- *This skill enables true autonomous self-healing via QWEN/Gemma/WRE coordination with transparent UnDaoDu communication.*