self-diagnosis

name	self-diagnosis
description	自诊断 — 监控系统健康指标，检测异常模式，定位故障根因
version	1.0.0
license	MIT
metadata	{"author":"blackplume233","actant-tags":"diagnosis,monitoring,health-check,maintainer","layer":"kernel","agent":"maintainer"}

Self-Diagnosis

Overview

Monitor system health metrics, detect anomaly patterns, and locate root causes of failures.

Health Metrics

Metric	Source	Thresholds
CPU	Process / OS	> 90% sustained → alert
Memory	RSS, heap	> 80% of limit → warn
Disk	Workspace, logs, temp	< 10% free → alert
Process	Daemon, Agent PIDs	Not running → critical
Latency	RPC, ACP round-trip	> 5s → warn

Anomaly Detection Patterns

• Spike: Sudden jump in metric; compare to rolling baseline
• Drift: Gradual degradation over time
• Cascade: One failure triggers others; trace dependency chain
• Recurrence: Same error pattern repeats; correlate with recent changes

Log Analysis

• Parse stderr, daemon logs, Agent activity logs
• Extract error codes, stack traces, timestamps
• Group by error type; count frequency; identify hotspots

Dependency Chain Tracing

• Map: Daemon → Agent → MCP → external service
• On failure: walk upstream to find first failing component
• Report: "Agent X failed because MCP Y timed out; MCP Y failed because..."