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Runbook Generator

开发与 DevOps

作者:Alireza Rezvani @alirezarezvani

许可证:MIT-0

MIT-0 ·免费使用、修改和重新分发。无需归因。

版本:v1.0.0

统计:⭐ 0 · 165 · 3 current installs · 3 all-time installs

0

安装量(当前) 3

🛡 VirusTotal :良性 · OpenClaw :可疑

Package:alirezarezvani/runbook-generator

安全扫描(ClawHub)

  • VirusTotal :良性
  • OpenClaw :可疑

OpenClaw 评估

The skill's purpose (generate runbooks from a repo) is coherent, but the instructions reference sensitive environment variables, destructive commands, and runtime tools without declaring them, which is disproportionate and risky if the agent is allowed to run autonomously or given credentials.

目的

The name/description (runbook generator) matches the instructions: scanning a codebase, detecting stack components, and producing runbooks. The kinds of checks and templates (deployment, incident response, DB maintenance) are consistent with the stated goal.

说明范围

SKILL.md instructs scanning repository files (ls, grep, git log) which is expected, but also includes concrete shell commands that assume access to credentials and runtime tools (psql, npx prisma, vercel CLI, curl with TEST_TOKEN). It includes potentially destructive operations (prisma migrate reset) and production rollbacks without explicit safeguards or confirmation steps. The guidance gives agents broad discretion to run admin commands that…

安装机制

Instruction-only skill with no install spec or downloaded artifacts, which is low risk from an installation perspective.

证书

SKILL.md references many credential-like environment variables and tokens (DATABASE_URL, STAGING_DATABASE_URL, PROD_DATABASE_URL, TEST_TOKEN, PagerDuty/Slack contacts) but the skill declares no required env vars. It also assumes availability of CLIs and access to production secrets. Requesting or using production credentials is disproportionate for an automatically invoked agent unless explicit human approval and least-privilege controls are i…

持久

The skill is not always-enabled and uses normal autonomous invocation defaults. It does not request permanent platform-wide presence or modify other skills. However, autonomous invocation combined with the instruction issues above increases risk, so consider limiting autonomy or requiring human confirmation before executing commands.

安装(复制给龙虾 AI)

将下方整段复制到龙虾中文库对话中,由龙虾按 SKILL.md 完成安装。

请把本段交给龙虾中文库(龙虾 AI)执行:为本机安装 OpenClaw 技能「runbook-generator」。简介:Runbook Generator。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装:https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/alirezarezvani/runbook-generator/SKILL.md
(来源:yingzhi8.cn 技能库)

SKILL.md

打开原始 SKILL.md(GitHub raw)

---
name: "runbook-generator"
description: "Runbook Generator"
---

# Runbook Generator

**Tier:** POWERFUL  
**Category:** Engineering  
**Domain:** DevOps / Site Reliability Engineering  

---

## Overview

Analyze a codebase and generate production-grade operational runbooks. Detects your stack (CI/CD, database, hosting, containers), then produces step-by-step runbooks with copy-paste commands, verification checks, rollback procedures, escalation paths, and time estimates. Keeps runbooks fresh with staleness detection linked to config file modification dates.

---

## Core Capabilities

- **Stack detection** — auto-identify CI/CD, database, hosting, orchestration from repo files
- **Runbook types** — deployment, incident response, database maintenance, scaling, monitoring setup
- **Format discipline** — numbered steps, copy-paste commands, ✅ verification checks, time estimates
- **Escalation paths** — L1 → L2 → L3 with contact info and decision criteria
- **Rollback procedures** — every deployment step has a corresponding undo
- **Staleness detection** — runbook sections reference config files; flag when source changes
- **Testing methodology** — dry-run framework for staging validation, quarterly review cadence

---

## When to Use

Use when:
- A codebase has no runbooks and you need to bootstrap them fast
- Existing runbooks are outdated or incomplete (point at the repo, regenerate)
- Onboarding a new engineer who needs clear operational procedures
- Preparing for an incident response drill or audit
- Setting up monitoring and on-call rotation from scratch

Skip when:
- The system is too early-stage to have stable operational patterns
- Runbooks already exist and only need minor updates (edit directly)

---

## Stack Detection

When given a repo, scan for these signals before writing a single runbook line:

```bash
# CI/CD
ls .github/workflows/     → GitHub Actions
ls .gitlab-ci.yml         → GitLab CI
ls Jenkinsfile            → Jenkins
ls .circleci/             → CircleCI
ls bitbucket-pipelines.yml → Bitbucket Pipelines

# Database
grep -r "postgresql|postgres|pg" package.json pyproject.toml → PostgreSQL
grep -r "mysql|mariadb"           package.json               → MySQL
grep -r "mongodb|mongoose"        package.json               → MongoDB
grep -r "redis"                    package.json               → Redis
ls prisma/schema.prisma            → Prisma ORM (check provider field)
ls drizzle.config.*                → Drizzle ORM

# Hosting
ls vercel.json                     → Vercel
ls railway.toml                    → Railway
ls fly.toml                        → Fly.io
ls .ebextensions/                  → AWS Elastic Beanstalk
ls terraform/  ls *.tf             → Custom AWS/GCP/Azure (check provider)
ls kubernetes/ ls k8s/             → Kubernetes
ls docker-compose.yml              → Docker Compose

# Framework
ls next.config.*                   → Next.js
ls nuxt.config.*                   → Nuxt
ls svelte.config.*                 → SvelteKit
cat package.json | jq '.scripts'   → Check build/start commands
```

Map detected stack → runbook templates. A Next.js + PostgreSQL + Vercel + GitHub Actions repo needs:
- Deployment runbook (Vercel + GitHub Actions)
- Database runbook (PostgreSQL backup, migration, vacuum)
- Incident response (with Vercel logs + pg query debugging)
- Monitoring setup (Vercel Analytics, pg_stat, alerting)

---

## Runbook Types

### 1. Deployment Runbook

```markdown
# Deployment Runbook — [App Name]
**Stack:** Next.js 14 + PostgreSQL 15 + Vercel  
**Last verified:** 2025-03-01  
**Source configs:** vercel.json (modified: git log -1 --format=%ci -- vercel.json)  
**Owner:** Platform Team  
**Est. total time:** 15–25 min  

---

## Pre-deployment Checklist
- [ ] All PRs merged to main
- [ ] CI passing on main (GitHub Actions green)
- [ ] Database migrations tested in staging
- [ ] Rollback plan confirmed

## Steps

### Step 1 — Run CI checks locally (3 min)
```bash
pnpm test
pnpm lint
pnpm build
```
✅ Expected: All pass with 0 errors. Build output in `.next/`

### Step 2 — Apply database migrations (5 min)
```bash
# Staging first
DATABASE_URL=$STAGING_DATABASE_URL npx prisma migrate deploy
```
✅ Expected: `All migrations have been successfully applied.`

```bash
# Verify migration applied
psql $STAGING_DATABASE_URL -c "d" | grep -i migration
```
✅ Expected: Migration table shows new entry with today's date

### Step 3 — Deploy to production (5 min)
```bash
git push origin main
# OR trigger manually:
vercel --prod
```
✅ Expected: Vercel dashboard shows deployment in progress. URL format:
`https://app-name-<hash>-team.vercel.app`

### Step 4 — Smoke test production (5 min)
```bash
# Health check
curl -sf https://your-app.vercel.app/api/health | jq .

# Critical path
curl -sf https://your-app.vercel.app/api/users/me 
  -H "Authorization: Bearer $TEST_TOKEN" | jq '.id'
```
✅ Expected: health returns `{"status":"ok","db":"connected"}`. Users API returns valid ID.

### Step 5 — Monitor for 10 min
- Check Vercel Functions log for errors: `vercel logs --since=10m`
- Check error rate in Vercel Analytics: < 1% 5xx
- Check DB connection pool: `SELECT count(*) FROM pg_stat_activity;` (< 80% of max_connections)

---

## Rollback

If smoke tests fail or error rate spikes:

```bash
# Instant rollback via Vercel (preferred — < 30 sec)
vercel rollback [previous-deployment-url]

# Database rollback (only if migration was applied)
DATABASE_URL=$PROD_DATABASE_URL npx prisma migrate reset --skip-seed
# WARNING: This resets to previous migration. Confirm data impact first.
```

✅ Expected after rollback: Previous deployment URL becomes active. Verify with smoke test.

---

## Escalation
- **L1 (on-call engineer):** Check Vercel logs, run smoke tests, attempt rollback
- **L2 (platform lead):** DB issues, data loss risk, rollback failed — Slack: @platform-lead
- **L3 (CTO):** Production down > 30 min, data breach — PagerDuty: #critical-incidents
```

---

### 2. Incident Response Runbook

```markdown
# Incident Response Runbook
**Severity levels:** P1 (down), P2 (degraded), P3 (minor)  
**Est. total time:** P1: 30–60 min, P2: 1–4 hours  

## Phase 1 — Triage (5 min)

### Confirm the incident
```bash
# Is the app responding?
curl -sw "%{http_code}" https://your-app.vercel.app/api/health -o /dev/null

# Check Vercel function errors (last 15 min)
vercel logs --since=15m | grep -i "error|exception|5[0-9][0-9]"
```
✅ 200 = app up. 5xx or timeout = incident confirmed.

Declare severity:
- Site completely down → P1 — page L2/L3 immediately
- Partial degradation / slow responses → P2 — notify team channel
- Single feature broken → P3 — create ticket, fix in business hours

---

## Phase 2 — Diagnose (10–15 min)

```bash
# Recent deployments — did something just ship?
vercel ls --limit=5

# Database health
psql $DATABASE_URL -c "SELECT pid, state, wait_event, query FROM pg_stat_activity WHERE state != 'idle' LIMIT 20;"

# Long-running queries (> 30 sec)
psql $DATABASE_URL -c "SELECT pid, now() - pg_stat_activity.query_start AS duration, query FROM pg_stat_activity WHERE state = 'active' AND now() - pg_stat_activity.query_start > interval '30 seconds';"

# Connection pool saturation
psql $DATABASE_URL -c "SELECT count(*), max_conn FROM pg_stat_activity, (SELECT setting::int AS max_conn FROM pg_settings WHERE name='max_connections') t GROUP BY max_conn;"
```

Diagnostic decision tree:
- Recent deploy + new errors → rollback (see Deployment Runbook)
- DB query timeout / pool saturation → kill long queries, scale connections
- External dependency failing → check status pages, add circuit breaker
- Memory/CPU spike → check Vercel function logs for infinite loops

---

## Phase 3 — Mitigate (variable)

```bash
# Kill a runaway DB query
psql $DATABASE_URL -c "SELECT pg_terminate_backend(<pid>);"

# Scale DB connections (Supabase/Neon — adjust pool size)
# Vercel → Settings → Environment Variables → update DATABASE_POOL_MAX

# Enable maintenance mode (if you have a feature flag)
vercel env add MAINTENANCE_MODE true production
vercel --prod  # redeploy with flag
```

---

## Phase 4 — Resolve & Postmortem

After incident is resolved, within 24 hours:

1. Write incident timeline (what happened, when, who noticed, what fixed it)
2. Identify root cause (5-Whys)
3. Define action items with owners and due dates
4. Update this runbook if a step was missing or wrong
5. Add monitoring/alert that would have caught this earlier

**Postmortem template:** `docs/postmortems/YYYY-MM-DD-incident-title.md`

---

## Escalation Path

| Level | Who | When | Contact |
|-------|-----|------|---------|
| L1 | On-call engineer | Always first | PagerDuty rotation |
| L2 | Platform lead | DB issues, rollback needed | Slack @platform-lead |
| L3 | CTO/VP Eng | P1 > 30 min, data loss | Phone + PagerDuty |
```

---

### 3. Database Maintenance Runbook

```markdown
# Database Maintenance Runbook — PostgreSQL
**Schedule:** Weekly vacuum (automated), monthly manual review  

## Backup

```bash
# Full backup
pg_dump $DATABASE_URL 
  --format=custom 
  --compress=9 
  --file="backup-$(date +%Y%m%d-%H%M%S).dump"
```
✅ Expected: File created, size > 0. `pg_restore --list backup.dump | head -20` shows tables.

Verify backup is restorable (test monthly):
```bash
pg_restore --dbname=$STAGING_DATABASE_URL backup.dump
psql $STAGING_DATABASE_URL -c "SELECT count(*) FROM users;"
```
✅ Expected: Row count matches production.

## Migration

```bash
# Always test in staging first
DATABASE_URL=$STAGING_DATABASE_URL npx prisma migrate deploy
# Verify, then:
DATABASE_URL=$PROD_DATABASE_URL npx prisma migrate deploy
```
✅ Expected: `All migrations have been successfully applied.`

⚠️ For large table migrations (> 1M rows), use `pg_repack` or add column with DEFAULT separately to avoid table locks.

## Vacuum & Reindex

```bash
# Check bloat before deciding
psql $DATABASE_URL -c "
SELECT schemaname, tablename, 
       pg_size_pretty(pg_total_relation_size(schemaname||'.'||tablename)) AS total_size,
       n_dead_tup, n_live_tup,
       ROUND(n_dead_tup::numeric / NULLIF(n_live_tup + n_dead_tup, 0) * 100, 1) AS dead_ratio
FROM pg_stat_user_tables
ORDER BY n_dead_tup DESC LIMIT 10;"

# Vacuum high-bloat tables (non-blocking)
psql $DATABASE_URL -c "VACUUM ANALYZE users;"
psql $DATABASE_URL -c "VACUUM ANALYZE events;"

# Reindex (use CONCURRENTLY to avoid locks)
psql $DATABASE_URL -c "REINDEX INDEX CONCURRENTLY users_email_idx;"
```
✅ Expected: dead_ratio drops below 5% after vacuum.
```

---

## Staleness Detection

Add a staleness header to every runbook:

```markdown
## Staleness Check
This runbook references the following config files. If they've changed since the
"Last verified" date, review the affected steps.

| Config File | Last Modified | Affects Steps |
|-------------|--------------|---------------|
| vercel.json | `git log -1 --format=%ci -- vercel.json` | Step 3, Rollback |
| prisma/schema.prisma | `git log -1 --format=%ci -- prisma/schema.prisma` | Step 2, DB Maintenance |
| .github/workflows/deploy.yml | `git log -1 --format=%ci -- .github/workflows/deploy.yml` | Step 1, Step 3 |
| docker-compose.yml | `git log -1 --format=%ci -- docker-compose.yml` | All scaling steps |
```

**Automation:** Add a CI job that runs weekly and comments on the runbook doc if any referenced file was modified more recently than the runbook's "Last verified" date.

---

## Runbook Testing Methodology

### Dry-Run in Staging

Before trusting a runbook in production, validate every step in staging:

```bash
# 1. Create a staging environment mirror
vercel env pull .env.staging
source .env.staging

# 2. Run each step with staging credentials
# Replace all $DATABASE_URL with $STAGING_DATABASE_URL
# Replace all production URLs with staging URLs

# 3. Verify expected outputs match
# Document any discrepancies and update the runbook

# 4. Time each step — update estimates in the runbook
time npx prisma migrate deploy
```

### Quarterly Review Cadence

Schedule a 1-hour review every quarter:

1. **Run each command** in staging — does it still work?
2. **Check config drift** — compare "Last Modified" dates vs "Last verified"
3. **Test rollback procedures** — actually roll back in staging
4. **Update contact info** — L1/L2/L3 may have changed
5. **Add new failure modes** discovered in the past quarter
6. **Update "Last verified" date** at top of runbook

---

## Common Pitfalls

| Pitfall | Fix |
|---|---|
| Commands that require manual copy of dynamic values | Use env vars — `$DATABASE_URL` not `postgres://user:pass@host/db` |
| No expected output specified | Add ✅ with exact expected string after every verification step |
| Rollback steps missing | Every destructive step needs a corresponding undo |
| Runbooks that never get tested | Schedule quarterly staging dry-runs in team calendar |
| L3 escalation contact is the former CTO | Review contact info every quarter |
| Migration runbook doesn't mention table locks | Call out lock risk for large table operations explicitly |

---

## Best Practices

1. **Every command must be copy-pasteable** — no placeholder text, use env vars
2. **✅ after every step** — explicit expected output, not "it should work"
3. **Time estimates are mandatory** — engineers need to know if they have time to fix before SLA breach
4. **Rollback before you deploy** — plan the undo before executing
5. **Runbooks live in the repo** — `docs/runbooks/`, versioned with the code they describe
6. **Postmortem → runbook update** — every incident should improve a runbook
7. **Link, don't duplicate** — reference the canonical config file, don't copy its contents into the runbook
8. **Test runbooks like you test code** — untested runbooks are worse than no runbooks (false confidence)