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incident-response事件响应

Agent Skill

incident-response 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

15,528

周安装

647

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下载量

5,176
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:incident-response(事件响应)
来源仓库:https://github.com/chunhualiao/incident-response
安装命令:
openclaw skills install incident-response
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install incident-response

简介

incident-response 提供 OpenClaw 系统故障的结构化处理流程,包括调查、恢复与预防阶段指导。

  • 适用于配置丢失、崩溃或性能下降等运维问题排查与应急响应场景。
  • 通过 clawhub 安装后按 7 阶段流程逐步执行,需结合日志分析与系统状态检查使用。
  • 使用前应确认故障现象与影响范围,避免盲目操作加剧系统不稳定或数据损坏。
  • 该技能为方法论支持,不替代实际诊断工具,建议配合监控告警系统协同使用。

SKILL.md

name
incident-response
version
1.0.0
description
Structured incident response for OpenClaw system failures. Use when a user reports something broken, missing, changed, or misbehaving — config loss, agent routing failures, binding changes, gateway crashes, missing settings, or any system regression. Follows a strict 7-phase loop: Triage → Evidence → 5 Whys → Restore → Prevent → Monitor → Document. Triggers on: "investigate", "why did X stop working", "something changed", "bindings lost", "gateway down", "gateway crashed", "setting disappeared", "something disappeared", "fix this", "who changed X", "root cause", "audit", "misconfigured", "agent not responding".
owner_agent
any agent with exec access to the affected system

Incident Response

Seven phases, in order. Never skip. Never assume — follow the evidence.

Outputs produced by this skill:

  • Root cause statement (5 Whys chain with evidence citations)
  • Restore confirmation (what was restored, verified working)
  • Prevention commit (git commit hash of guard/rule added)
  • Monitoring cron (job ID + schedule)
  • Learning entry (appended to ~/.openclaw/learnings/rules.md)

Phase 0: Triage (2 min)

Check current state FIRST before investigating history.

# Is it actually broken right now?
openclaw status
ssh "<remote-host>" "launchctl list | grep openclaw"
# Test with correct protocol (check source: HTTP vs HTTPS?)

If currently working → report "recovered, investigating cause." If still broken → proceed.

Phase 1: Evidence Collection

Gather hard evidence from four sources:

1a. Config backups timeline

# See binding/setting counts over time
ssh "<remote-host>" "python3 << 'EOF'
import json, glob, os
for f in sorted(glob.glob('~/.openclaw/config-backups/openclaw-*.json'), key=os.path.getmtime):
    d = json.load(open(f))
    import datetime
    dt = datetime.datetime.fromtimestamp(os.path.getmtime(f)).strftime('%Y-%m-%d %H:%M')
    # Customize: bindings, agents, channels, etc.
    count = len(d.get('bindings', []))
    ids = [b.get('agentId') for b in d.get('bindings', [])]
    print(f'{dt} [{count}] {ids}')
EOF"

1b. Git audit trail

ssh "<remote-host>" "cd ~/.openclaw && git log --oneline -20"
ssh "<remote-host>" "cd ~/.openclaw && git diff <commit-a> <commit-b> -- openclaw.json | grep '^[+-]' | grep -v '^---\|^+++'"

1c. Session logs (who did what)

# Find sessions that touched the broken config key
ssh "<remote-host>" "rg -rl 'keyword' ~/.openclaw/agents/*/sessions/*.jsonl | head -5"

# Extract tool calls from a session
ssh "<remote-host>" "python3 << 'EOF'
import json
for line in open('SESSION.jsonl'):
    obj = json.loads(line)
    if obj.get('type') != 'message': continue
    for block in obj.get('message',{}).get('content',[]):
        if block.get('type') == 'toolCall' and block.get('name') in ['Write','Edit','gateway','exec']:
            print(obj['timestamp'], block['name'], str(block.get('input',''))[:200])
EOF"

1d. Config backup diff (find the exact moment of change)

# Compare before/after a suspicious backup
python3 -c "
import json
a = json.load(open('backup-before.json'))
b = json.load(open('backup-after.json'))
# Compare specific field
print('Before:', a.get('bindings'))
print('After:', b.get('bindings'))
"

Stop and document: Who changed what, when, which session, which tool call.

Phase 2: 5 Whys Analysis

Write each "why" as a statement of fact backed by evidence from Phase 1.

Why 1: [Symptom] — e.g. "Bindings dropped from 17 to 1"
  Evidence: backup timestamp + count

Why 2: [Immediate cause] — e.g. "A full config replacement was written at 09:38 PST"
  Evidence: backup mtime + content diff

Why 3: [Mechanism] — e.g. "the agent wrote a new config from scratch, not from current config"
  Evidence: session log tool call + content

Why 4: [System gap] — e.g. "config-validate.sh --merge had no guard against binding count drops"
  Evidence: script inspection showing no such check

Why 5: [Root cause] — e.g. "No automated detection existed between when the config was written and the next user report"
  Evidence: no monitoring cron, no git at the time

Rule: Every "why" must cite a specific file, log entry, timestamp, or command output. No assumptions.

Phase 3: Restore

Restore to last known-good state using backup timeline from Phase 1.

# Restore specific fields (always merge, never replace)
PATCH=$(python3 -c "
import json
good = json.load(open('/path/to/good-backup.json'))
patch = {'bindings': good['bindings']}  # customize field
print(json.dumps(patch))
")
echo "$PATCH" | ssh "<remote-host>" "~/.openclaw/scripts/config-validate.sh --merge"

# Restart gateway
ssh "<remote-host>" "launchctl stop ai.openclaw.gateway && sleep 2 && launchctl start ai.openclaw.gateway"
ssh "<remote-host>" "launchctl list | grep ai.openclaw.gateway"  # verify exit code 0

Verify restore: Check that the restored value matches the good backup. Re-run the user's original failing action.

Phase 4: Prevention

Add guards proportional to the severity and recurrence risk. See references/prevention-patterns.md for full patterns. Quick reference:

For config fields that must not decrease: Add guard to config-validate.sh --merge (see references for template)

For agent behavior rules: Add to ~/.openclaw/agents/<id>/agent/SOUL.md as a Hard Rule (HR-NNN)

For recurring mistakes: Add to ~/.openclaw/learnings/rules.md with category and date

For schema validation gaps: Update config-validate.sh valid_keys list after verifying against DeepWiki

Always commit prevention changes to git:

ssh "<remote-host>" "cd ~/.openclaw && git add -A && git commit -m 'prevention: <what was added> after <incident>'"

Phase 5: Monitor

Set a recurring cron job that runs until user confirms "good enough" (minimum 7 days, 30 days for recurring incidents).

Cron job structure:
- Schedule: every 24h (or every N hours for high-severity)
- Task: check specific metric → compare to baseline → if degraded: restore + 5-why → report
- Report channel: sessions_send to your preferred channel (Signal, Telegram, Discord)
- Auto-escalate: if same fix needed 3+ days in a row → upgrade prevention measure
- Termination: user explicitly says "stop monitoring" or N days without incident

See references/cron-template.md for the full cron job prompt template.

Phase 6: Document

Write to ~/.openclaw/learnings/rules.md if a Hard Rule should be added:

  • Category: HR (Hard Rule, recurring) or SR (Soft Rule, first offense)
  • Include: what triggered, what the rule is, date learned, why it matters

Update MEMORY.md with incident summary if it's systemic.


Configuration

No persistent configuration required. Adapt the following to your environment:

VariableDescriptionExample
Remote hostSSH target for remote investigations<remote-host> → your Titan/server hostname
Config backup pathWhere OpenClaw stores automatic config backups~/.openclaw/config-backups/
Session keyYour messaging session key for cron reportsagent:main-signal:signal:<your-number>
Learnings pathWhere rules are persisted~/.openclaw/learnings/rules.md

See references/cron-template.md for full cron report configuration.


Quick Diagnosis Checklists

See references/checklists.md for:

  • Gateway crash checklist
  • Binding loss checklist
  • Config key disappeared checklist
  • Agent routing wrong checklist
  • Vector search not finding content checklist

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

70.51%
按下载量换算3,650

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

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权限和风险

敏感数据

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安装前确认

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