Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/misonl/ling/nodejs-best-practicesnpx skills add MisonL/Ling --skill nodejs-best-practicesgit clone --depth 1 https://github.com/MisonL/LingWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00041 | $0.02449 |
| Opus 5 | $0.00020 | $0.01224 |
| Sonnet 5 | $0.00008 | $0.00490 |
| Haiku 4.5 | $0.00004 | $0.00245 |
Grade A, and why
nodejs-best-practices scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 334 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Node.js 最佳实践
面向 2025 的 Node.js 开发原则与决策方法。
学习如何思考,不要只记代码套路。
[WARN] 本技能使用方式
本技能教授的是决策原则,不是固定代码模板。
- 需求不明确时,先向用户确认偏好
- 根据上下文(Context)选择框架与模式
- 不要每次都默认同一套方案
1. 框架选型(2025)
决策树
你要构建什么?
|
+-- Edge/Serverless(边缘/无服务器,Cloudflare、Vercel)
| +-- Hono(零依赖、冷启动极快)
|
+-- 高性能 API
| +-- Fastify(通常比 Express 快 2-3 倍)
|
+-- 企业协作/团队熟悉度优先
| +-- NestJS(结构化、DI、装饰器)
|
+-- 传统/稳定/生态最大化
| +-- Express(成熟、middleware 最多)
|
+-- 前后端一体
+-- Next.js API Routes 或 tRPC
对比原则
| 维度 | Hono | Fastify | Express |
|---|---|---|---|
| 适用场景 | Edge、serverless | 性能优先 | 传统、学习 |
| 冷启动 | 最快 | 快 | 中等 |
| 生态 | 成长中 | 较好 | 最大 |
| TypeScript | 原生支持 | 优秀 | 良好 |
| 学习曲线 | 低 | 中 | 低 |
选型前必须询问:
- 部署目标是什么?
- 冷启动时间是否关键?
- 团队是否有既有经验?
- 是否存在需要维护的遗留代码?
2. 运行时考量(2025)
原生 TypeScript
Node.js 22+: --experimental-strip-types
+-- 可直接运行 .ts 文件
+-- 简单项目可免构建步骤
+-- 适用:脚本、简单 API
模块系统决策
ESM(import/export)
+-- 现代标准
+-- 更好的 tree-shaking
+-- 异步模块加载
+-- 适用:新项目
CommonJS(require)
+-- 遗留兼容性更好
+-- 对部分 npm 包支持更成熟
+-- 适用:既有代码库、特定边界场景
Runtime 选择
| Runtime | 适用场景 |
|---|---|
| Node.js | 通用场景、生态最大 |
| Bun | 性能优先、内置 bundler |
| Deno | 安全优先、内置 TypeScript |
3. 架构原则
分层结构概念
请求流(Request Flow):
|
+-- Controller/Route 层
| +-- 处理 HTTP 细节
| +-- 在边界做输入校验
| +-- 调用 service 层
|
+-- Service 层
| +-- 承载业务逻辑
| +-- 与框架解耦
| +-- 调用 repository 层
|
+-- Repository 层
+-- 仅处理数据访问
+-- 数据库查询
+-- ORM 交互
为什么重要
- 可测性(Testability): 可独立 mock 每一层
- 灵活性(Flexibility): 更换数据库不影响业务层
- 清晰性(Clarity): 每层职责单一
何时简化
- 小型脚本 -> 单文件可接受
- 原型验证 -> 可降低结构复杂度
- 始终追问:“这个项目会继续增长吗?”
4. 错误处理原则
集中式错误处理
Pattern:
+-- 定义自定义错误类
+-- 各层都可 throw
+-- 在顶层统一 catch(middleware)
+-- 输出一致的响应格式
错误响应哲学
Client gets:
+-- 合理的 HTTP 状态码
+-- 可程序化处理的错误码
+-- 对用户友好的提示
+-- 不暴露内部细节(安全要求)
Logs get:
+-- 完整堆栈信息
+-- 请求上下文
+-- 用户 ID(如适用)
+-- 时间戳
状态码选择
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 334 lines · 41 tokens per session scan A afd79a57be0c
nodejs-best-practices is a skill published in the GitHub repository MisonL/Ling (9 stars, last pushed 5mo ago), licensed MIT. It adds 41 tokens to every session and 2,449 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…