Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Build reliable backend services with proper error handling, security, and observability.
Build reliable backend services with proper error handling, security, and observability.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Never expose stack traces to clients—log internally, return generic message Structured error responses: code, message, request ID—enables debugging without leaking Fail fast on bad input—validate at entry point, not deep in business logic Unexpected errors: 500 + alert—expected errors: appropriate 4xx
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
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
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
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
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
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
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
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
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
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
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
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
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Largest current source with strong distribution and engagement signals.