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首页> AI教程> 生产就绪度元技能:确保服务稳定性 - Openclaw Skills

生产就绪度元技能:确保服务稳定性 - Openclaw Skills

时间:2026-03-26 18:48:01 作者:互联网

什么是 生产就绪度?

生产就绪度元技能作为一个综合编排层,旨在确保服务在进入生产流量之前已全面运行。该技能不是手动检查每个配置,而是利用 Openclaw Skills 生态系统将技术问题(如结构化日志、熔断和密钥管理)路由到专业的子代理。它将这些细颗粒度的输入综合为最终的发布/不发布评估,为开发人员提供关于服务健康和可靠性的统一报告。

通过协调日志、错误处理、性能和安全方面的领域专家,该技能消除了服务移交过程中对部落知识的需求。它确保每个服务都能自我观察,从瞬时故障中自动恢复,并有效地向编排器传达其健康状况,使其成为维护高可用性环境的重要工具。

下载入口:https://github.com/openclaw/skills/tree/main/skills/wpank/production-readiness

安装与下载

1. ClawHub CLI

从源直接安装技能的最快方式。

npx clawhub@latest install production-readiness

2. 手动安装

将技能文件夹复制到以下位置之一

全局模式 ~/.openclaw/skills/ 工作区 /skills/

优先级:工作区 > 本地 > 内置

3. 提示词安装

将此提示词复制到 OpenClaw 即可自动安装。

请帮我使用 Clawhub 安装 production-readiness。如果尚未安装 Clawhub,请先安装(npm i -g clawhub)。

生产就绪度 应用场景

生产就绪度 工作原理
  1. 该技能根据项目上下文启动日志、性能和安全的专业子技能。
  2. 验证健康检查端点的实现,包括存活、就绪和启动探针。
  3. 代理审核弹性模式,如熔断器、带抖动的重试策略和出站超时。
  4. 执行安全扫描以确保密钥外部化,且配置更改不需要重新部署。
  5. 通过检查操作手册、SLO 定义和黄金信号仪表板的存在来验证运营就绪情况。
  6. 该技能将所有发现综合到结构化报告中,并分配从 L1 (MVP) 到 L4 (优化) 的成熟度级别。

生产就绪度 配置指南

要将此元技能添加到您的环境中,请使用 Openclaw Skills 中心 CLI:

npx clawhub@latest install production-readiness

生产就绪度 数据架构与分类体系

该技能将其评估数据组织到基于成熟度的分类法中,将专业技能输出映射到运营要求:

数据类别 描述
健康与生命周期 探针检查结果和优雅停机排空验证
弹性矩阵 熔断、限流和背压机制的审计
密钥审计 Vault 集成和外部化配置状态的验证
数据安全 备份策略、RPO/RTO 和迁移可逆性的文档
运营文档 操作手册、SLO 和升级矩阵的链接
成熟度评级 基于累积审计结果的最终 L1-L4 分类
name: production-readiness
model: reasoning
description: Meta-skill that orchestrates logging, monitoring, error handling, performance, security, deployment, and testing skills to ensure a service is fully production-ready before launch. Use before first deploy, major releases, quarterly reviews, or after incidents.

Production Readiness (Meta-Skill)

Coordinates all operational concerns into a single readiness review. Instead of duplicating domain expertise, this skill routes to specialized skills and agents for each area, then synthesizes results into a unified go/no-go assessment.

Installation

OpenClaw / Moltbot / Clawbot

npx clawhub@latest install production-readiness

Purpose

Ensure a service is production-ready by systematically checking every operational concern — logging, error handling, performance, security, deployment, testing, and documentation — before traffic hits it.

A production-ready service:


When to Use

Trigger Context
Before first deploy New service going to production for the first time
Before major release Significant feature or architectural change shipping
Quarterly production review Scheduled audit of existing services
After incident Post-incident hardening to prevent recurrence
Dependency upgrade Major framework, runtime, or infrastructure change
Team handoff Transferring ownership of a service to another team

Orchestration Flow

Run each area sequentially or in parallel. Each step delegates to a specialized skill or agent — this skill does not re-implement their logic.

┌─────────────────────────────────────────────────┐
│              Production Readiness Review         │
├─────────────────────────────────────────────────┤
│                                                  │
│  1. Logging & Observability ──? logging-observability skill
│  2. Error Handling ───────────? error-handling-patterns skill
│  3. Performance ──────────────? performance-agent
│  4. Security ─────────────────? security-review meta-skill
│  5. Deployment ───────────────? deployment-agent + docker-expert skill
│  6. Testing ──────────────────? testing-workflow meta-skill
│  7. Documentation ────────────? /generate-docs command
│                                                  │
│  ──? Synthesize results into go/no-go report     │
└─────────────────────────────────────────────────┘

Step Details

  1. Logging & Observability — Structured logging, log levels, correlation IDs, metrics endpoints, distributed tracing, alerting rules
  2. Error Handling — Global error boundaries, retry policies, dead-letter queues, error classification, user-facing error messages
  3. Performance — Load testing results, P95/P99 latency baselines, memory/CPU profiling, database query analysis, caching strategy
  4. Security — Auth/authz verification, input validation, dependency audit, secrets management, OWASP top-10 review
  5. Deployment — Container hardening, rollback strategy, blue-green/canary configuration, infrastructure-as-code review
  6. Testing — Unit/integration/e2e coverage, contract tests, chaos/failure injection, smoke tests in staging
  7. Documentation — API docs, runbooks, architecture diagrams, on-call playbooks, ADRs for key decisions

Skill Routing Table

Concern Skill / Agent Path
Logging & Observability logging-observability ai/skills/tools/logging-observability/SKILL.md
Error Handling error-handling-patterns ai/skills/backend/error-handling-patterns/SKILL.md
Performance performance-agent ai/agents/performance/
Security security-review ai/skills/meta/security-review/SKILL.md
Deployment (containers) docker-expert ai/skills/devops/docker/SKILL.md
Deployment (pipelines) deployment-agent ai/agents/deployment/
Testing testing-workflow ai/skills/testing/testing-workflow/SKILL.md
Rate Limiting rate-limiting-patterns ai/skills/backend/rate-limiting-patterns/SKILL.md
Documentation /generate-docs ai/commands/documentation/

Routing rule: Read the target skill first, follow its instructions, then return results here for synthesis.


Production Readiness Checklist

Health & Lifecycle

Resilience

Configuration & Secrets

Data Safety

Operational Readiness


Maturity Levels

Level Name Requirements
L1 MVP Health check, basic logging, error handling, manual deploy, unit tests, README
L2 Stable Structured logging, metrics, graceful shutdown, CI/CD pipeline, integration tests, runbooks
L3 Resilient Distributed tracing, circuit breakers, auto-scaling, chaos testing, SLOs, on-call rotation
L4 Optimized Adaptive rate limiting, predictive alerting, canary deploys, full observability, error budgets, postmortem culture

Progression Guidance


Incident Response

On-Call Rotation

Escalation Matrix

Severity Response Time Escalation After Stakeholder Notification
SEV-1 (outage) 15 min 30 min Immediate — exec + customers
SEV-2 (degraded) 30 min 1 hour Within 1 hour — eng lead
SEV-3 (minor) 4 hours Next business day Daily standup
SEV-4 (cosmetic) Next sprint N/A Backlog

Postmortem Template

## Incident: [Title]
**Date:** YYYY-MM-DD | **Duration:** X hours | **Severity:** SEV-N

### Summary
One-paragraph description of what happened and impact.

### Timeline
- HH:MM — First alert fired
- HH:MM — Engineer paged, investigation started
- HH:MM — Root cause identified
- HH:MM — Mitigation applied
- HH:MM — Full resolution confirmed

### Root Cause
What broke and why. Link to code/config change if applicable.

### Impact
- Users affected: N
- Revenue impact: $X (if applicable)
- SLO budget consumed: X%

### Action Items
| Action | Owner | Due Date | Status |
|--------|-------|----------|--------|
| Fix X  | @eng  | YYYY-MM-DD | Open |

### Lessons Learned
- What went well
- What went poorly
- Where we got lucky

NEVER Do

  1. NEVER skip health checks — every service must expose health endpoints; no exceptions for "simple" services
  2. NEVER store secrets in code or container images — use a secrets manager; never default env vars with real values
  3. NEVER deploy without a rollback plan — if you cannot roll back in under 5 minutes, you are not ready to deploy
  4. NEVER ignore error budget violations — when the error budget is exhausted, freeze feature work and fix reliability
  5. NEVER treat logging as optional — a service without structured logging is a service you cannot debug at 3 AM
  6. NEVER go to production without runbooks — if on-call cannot resolve the top 5 failure modes without the original author, the service is not production-ready
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