360 Secure SkillHub
360 安全技能中心

Incident Fupan (事故复盘) — Structured Root Cause Analysis

核心功能:按标准化流程完成结构化根因分析,生成含时间线、5Whys根因、影响评估、整改措施的合规复盘报告,提取可落地防御规则。典型场景:生产故障/outage、Agent失误致实际损失、近失事件、过往事故定期复盘。输入为复盘请求及相关证据(日志、Git状态等),输出匹配用户语言的Markdown报告,自动存储至指定目录。

scytheshan-pixel
scytheshan-pixel
热度 73.80
最近更新 2026-05-17 13:15:28
分类:数据依赖:代码执行 / 读写文件 / 内部调用大模型应用场景:数据处理 / 报告撰写

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add incident-fupan
Metadata
name
incident-fupan
description
事故复盘 / Incident Fupan — structured root cause analysis for production failures, outages, bugs, and near-misses. Use when: (1) 事故复盘 or incident review is needed, (2) a production incident just happened and needs root cause analysis, (3) an agent made a costly mistake and you want to prevent recurrence, (4) building safety rules or kill switches from incident patterns. Triggers on: 复盘, fupan, postmortem, incident review, root cause analysis, 事故分析. Generates a full report with timeline, 5 Whys root cause, impact assessment, fix/prevention actions, and new defensive rules. NOT for: routine debugging, feature planning, or non-incident analysis.

Incident Fupan (事故复盘)

Structured root cause analysis and prevention protocol for production incidents.

Language Rule

Report language matches the user's language. Chinese request → Chinese report. English → English.

When to Trigger

  • Production failure, outage, or unexpected loss
  • Agent mistake with real consequences (wrong deployment, fabricated output acted upon)
  • Near-miss that could have caused damage
  • Periodic review of past incidents to extract patterns

Postmortem Flow

Step 1: Gather Evidence

Before writing anything, collect raw evidence. Do NOT rely on memory or assumptions.

Required evidence (use tools to retrieve):

  • Logs: exec("grep -i 'error\|fatal\|exception' {logfile} | tail -50")
  • Git state: exec("git log --oneline -10"), exec("git diff HEAD~1 --stat")
  • Service state: exec("systemctl status {service}"), exec("ps aux | grep {process}")
  • Data files: read any CSVs, configs, or state files involved

Rule: Every factual claim in the postmortem must cite a source. Format: [Source: {filepath}:{line} or {command output}]

If evidence is unavailable (logs rotated, service restarted), explicitly mark: [Evidence unavailable: {reason}]

Step 2: Build Timeline

Construct a minute-by-minute (or hour-by-hour) timeline from evidence:

HH:MM UTC — {what happened} [Source: {evidence}]
HH:MM UTC — {what happened} [Source: {evidence}]
...
HH:MM UTC — Incident resolved / mitigated

Include: first symptom, detection, escalation, diagnosis, fix, verification.

Mark the detection gap: time between first symptom and human awareness. This is often the real problem.

Step 3: 5 Whys Root Cause

Drill down from symptom to root cause:

Why 1: {symptom happened} → Because {direct cause}
Why 2: {direct cause} → Because {deeper cause}
Why 3: {deeper cause} → Because {systemic issue}
Why 4: {systemic issue} → Because {process/design gap}
Why 5: {process/design gap} → Because {root cause}

Stop when you reach something you can change. If you reach "the model hallucinated" — that's not actionable. Go deeper: why was the output trusted without verification? Why was there no checkpoint?

Step 4: Write Report

Save to: ~/incidents/INC{NNN}_{TOPIC}_{YYYYMMDD}.md

Create ~/incidents/ if it doesn't exist.

See references/report-template.md for the full template with all required sections.

Report must include all 8 sections:

  1. Header (ID, severity, date, duration, status)
  2. Executive Summary (3 sentences max)
  3. Timeline with sources
  4. Impact Assessment (quantified: time lost, money lost, trust lost)
  5. 5 Whys Root Cause
  6. Fix (what was done immediately)
  7. Prevention (new rules, checks, or automation to prevent recurrence)
  8. Action Items (P0/P1/P2 with owners and deadlines)

Step 5: Extract Defensive Rules

The most valuable output of a postmortem is new rules that prevent recurrence.

Pattern: Incident → Rule → Enforcement mechanism

Examples from real incidents:

  • Unauthorized deployment → "All deploys require explicit human approval" → Gate in CI/CD
  • Fabricated data report → "All data claims must cite source file + row count" → L1 in Hallucination Guard
  • Session bloat causing errors → "Compact at 80% context usage" → Automated monitoring

See references/patterns.md for a library of incident-to-rule patterns.

Step 6: Reply and Store

  1. Save report file to ~/incidents/
  2. Reply to user with the full report
  3. Store key lessons to long-term memory
  4. If applicable: update AGENTS.md, TOOLS.md, or relevant skill with new rules

Severity Levels

Level Criteria Response Time
SEV1 Money lost, data corrupted, security breach Immediate
SEV2 Service down, wrong actions taken from bad data Within 1 hour
SEV3 Degraded performance, near-miss, wasted time >2h Within 24 hours
SEV4 Minor issue, caught before impact Next convenient time

Integration

  • Hallucination Guard: Incidents caused by agent fabrication → add to L1/L3 detection rules
  • War Room: After postmortem, use War Room to evaluate proposed prevention strategy
  • Postmortem → new rules → enforcement → fewer incidents → feedback loop

References