Iván

Backend

开发编程v1.0.0
作者:Iván更新于 2026-05-11backend@clawhub_ivangdavila/backend
代码生成后端开发#Observability

据 AlphaMoat 统计,截至 2026-09,Backend 累计下载 4,702 次、获 4 个星标,在全部 5,078 个 AI 技能中排名第 2,019 位,在「开发编程」分类(577 个)中排名第 259 位。

累计安装
148
累计下载
4,702
星标
4
全站排名
#2,019
全站前 40% · 「开发编程」前 45%
平台累计安装累计下载星标评论
ClawHub ↗1484,7023-
SkillHub ↗1454,5164—

各平台的计数口径不同,统计时间不一致。

这个技能是做什么的

这份静态清单覆盖输入校验、超时、重试、连接池、事务、缓存、限流、健康检查、日志、API 设计和最小权限。应结合架构和运行条件审阅,避免在日志记录敏感信息;对值使用参数化查询并验证动态标识符,不将单一措施视为完整防护。

资料发布于 2026-10-29

可以用来做什么

  • 审查 API 的错误返回、参数校验和超时策略
  • 梳理数据库、缓存、限流与健康检查实践
  • 评估日志、安全与服务可观测性清单

什么时候用

  • 需要制定后端服务设计或审查清单时
  • 建议可以按团队架构和运行约束逐项调整时
  • 实现过程中能确保敏感数据不进入日志并采用安全数据库查询时

示例提示词

以下是根据技能文档生成的示例,不代表实际运行结果。

根据给定服务说明整理一份后端可靠性审查清单,指出哪些建议需要团队架构复核;不要更改代码或配置。

月度数据趋势

累计下载4,702
2,7123,7814,8492026-03 · 累计下载 2,8592026-05 · 累计下载 3,6932026-06 · 累计下载 3,8602026-07 · 累计下载 4,2392026-08 · 累计下载 4,5242026-09 · 累计下载 4,70226-0326-09
星标4
3442026-03 · 星标 32026-05 · 星标 32026-06 · 星标 32026-07 · 星标 42026-08 · 星标 42026-09 · 星标 426-0326-09

2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。

月份累计下载环比星标
2026-094,702—4
2026-084,524+6.7%4
2026-074,239+9.8%4
2026-063,860+4.5%3
2026-053,693—3
2026-032,859—3

SKILL.md 原文

以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。

3.8 KB · ClawHub v1.0.0
---
name: Backend
description: Build reliable backend services with proper error handling, security, and observability.
metadata: {"clawdbot":{"emoji":"⚙️","os":["linux","darwin","win32"]}}
---

## Error Handling

- Never expose stack traces to clients—log internally, return generic message
- Structured error responses: code, message, request ID—enables debugging without leaking
展开全部(共 97 行)
- Fail fast on bad input—validate at entry point, not deep in business logic
- Unexpected errors: 500 + alert—expected errors: appropriate 4xx

## Input Validation

- Validate everything from outside—query params, headers, body, path params
- Whitelist valid input, don't blacklist bad—reject unknown fields
- Validate early, before any processing—save resources, clearer errors
- Size limits on all inputs—prevent memory exhaustion attacks

## Timeouts Everywhere

- Database queries: set timeout, typically 5-30s
- External HTTP calls: connect timeout + read timeout—don't wait forever
- Overall request timeout—gateway or middleware level
- Background jobs: max execution time—prevent zombie processes

## Retry Patterns

- Exponential backoff: 1s, 2s, 4s, 8s...—prevents thundering herd
- Add jitter: randomize delay—prevents synchronized retries
- Idempotency keys for non-idempotent operations—safe to retry
- Circuit breaker for failing dependencies—stop hammering, fail fast

## Database Practices

- Connection pooling: reuse connections—creating is expensive
- Transactions scoped minimal—hold locks briefly
- Read replicas for read-heavy workloads—separate read/write traffic
- Prepared statements always—SQL injection prevention, query plan cache

## Caching Strategy

- Cache invalidation strategy decided upfront—TTL, event-based, or both
- Cache at right layer: query result, computed value, HTTP response
- Cache stampede prevention—lock or probabilistic early expiration
- Monitor hit rate—low hit rate = wasted resources

## Rate Limiting

- Per-user/IP limits on expensive operations—login, signup, search
- Different limits for different operations—read vs write
- Return Retry-After header—tell clients when to retry
- Rate limit early in request pipeline—save resources

## Health Checks

- Liveness: is process running—restart if fails
- Readiness: can handle traffic—remove from load balancer if fails
- Startup probe for slow-starting services—don't kill during init
- Health checks fast and cheap—don't hit database on every probe

## Graceful Shutdown

- Stop accepting new requests first—drain load balancer
- Wait for in-flight requests to complete—with timeout
- Close database connections cleanly—prevent connection leaks
- SIGTERM handling: graceful; SIGKILL after timeout

## Logging

- Structured logs (JSON)—parseable by log aggregators
- Request ID in every log—trace request across services
- Log level appropriate: debug for dev, info/error for prod
- Sensitive data never logged—passwords, tokens, PII

## API Design

- Versioning strategy from day one—path (/v1/) or header
- Pagination for list endpoints—cursor or offset; include total count
- Consistent response format—same envelope everywhere
- Meaningful status codes—201 for create, 204 for delete, 404 for not found

## Security Hygiene

- Secrets from environment or vault—never in code or config files
- Dependencies updated regularly—automated with Dependabot/Renovate
- Principle of least privilege—service accounts with minimal permissions
- Authentication and authorization separated—who you are vs what you can do

## Observability

- Metrics: request count, latency percentiles, error rate—the RED method
- Distributed tracing for microservices—follow request across services
- Alerting on symptoms, not causes—high error rate, not CPU usage
- Dashboards for operational visibility—know normal to spot abnormal

「开发编程」分类下的热门技能

Iván 的其他技能

数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。