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lidge-jun/codexclaw/plugins/codexclaw/skills/dev-backend/SKILL.md

cxc-dev-backend

Use it for deployment and engineering tasks; the detail page covers purpose, installation, and practical steps.

Source repository stars
9
Declared platforms
0
Static risk flags
0
Last source update
2026-08-03
Source checked
2026-08-04

Decision brief

What it does—and where it fits

Ownership boundary: This skill owns API design, app architecture, database optimization, error handling, middleware, queues, long-lived connections, and app-level observability/health hooks. Deployment strategy, rollback proof, rollout shape, SLOs, alert routing, incident respon…

Best for

    Not for

    • Tasks that require unconfirmed production actions or broad system permissions.
    • Environments where the pinned source and install steps cannot be inspected.

    Compatibility matrix

    Platform support, with evidence labels

    PlatformStatusEvidenceWhat to check
    CodexNot declaredNo explicit evidencePortability before use
    Claude CodeNot declaredNo explicit evidencePortability before use
    CursorNot declaredNo explicit evidencePortability before use
    Gemini CLINot declaredNo explicit evidencePortability before use
    Open the compatibility checker

    Installation

    Inspect first. Install second.

    The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

    Source-detected install commandSource
    npx skills add https://github.com/lidge-jun/codexclaw --skill "plugins/codexclaw/skills/dev-backend"
    Safe inspection promptEditorial

    Inspect the Agent Skill "cxc-dev-backend" from https://github.com/lidge-jun/codexclaw/blob/ecc644e7742dc516ea91777414baf3da1859a162/plugins/codexclaw/skills/dev-backend/SKILL.md at commit ecc644e7742dc516ea91777414baf3da1859a162. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

    Workflow

    What the source asks the agent to do

    1. 01

      Modular References

      Read api-design.md + anti-slop-backend.md first, then the relevant stack file. For C2 ordinary slices, crud-api.md alone suffices; read api-design.md/architecture.md for new API styles or C3+ work.

      Read api-design.md + anti-slop-backend.md first, then the relevant stack file. For C2 ordinary slices, crud-api.md alone suffices; read api-design.md/architecture.md for new API styles or C3+ work.When backend decisions depend on current external API docs, API lifecycle changes, LLM/RAG provider behavior, dependency freshness, or package/source evidence, read the active search skill and follow its query-rewrite,…
    2. 02

      0. Stack Detection & Architecture Clarification

      If config files exist → detect silently and proceed.

      Identify what's ambiguous from this list:Recommend one with reasoning: cite project context. e.g., "Small team → monolith + PostgreSQL + JWT is the simplest starting point."Over-engineering guard: A CRUD API probably doesn't need GraphQL + microservices + event sourcing. Simple → complex, not the reverse.
    3. 03

      Auto-detect (existing projects)

      If config files exist → detect silently and proceed.

      If config files exist → detect silently and proceed.
    4. 04

      Architecture Clarification (new or ambiguous projects)

      When the request has unspecified technology or unclear scope, clarify before coding:

      Identify what's ambiguous from this list:Recommend one with reasoning: cite project context. e.g., "Small team → monolith + PostgreSQL + JWT is the simplest starting point."Over-engineering guard: A CRUD API probably doesn't need GraphQL + microservices + event sourcing. Simple → complex, not the reverse.
    5. 05

      1. Architecture Decision

      Before coding, identify the right pattern:

      Connection registry: Track all active connections in-memory (Map by client/session ID). Required for graceful drain and debugging.Graceful drain on deploy: Stop accepting new connections → send "reconnect" frame to existing → wait drain timeout → close.Memory budget: Allocate max memory per connection (e.g., 2KB buffer). Monitor total; reject new connections when approaching limit.

    Permission review

    Static risk signals and limitations

    No configured static risk pattern was detected

    This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.

    Evidence record

    Why each signal appears

    EvidenceSourceComputedTestedEditorial
    SignalValueEvidence typeMeaning
    Quality score90/100ComputedDocumentation, specificity, maintenance, and trust rules
    Repository stars9SourceRepository attention, not individual Skill quality
    Compatibility0 platformsSourceDeclared in the catalog source record
    Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

    Pinned source

    Provenance and original SKILL.md

    Repository
    lidge-jun/codexclaw
    Skill path
    plugins/codexclaw/skills/dev-backend/SKILL.md
    Commit
    ecc644e7742dc516ea91777414baf3da1859a162
    License
    NOASSERTION
    Collected
    2026-08-04
    Default branch
    main
    View the original SKILL.md

    Dev-Backend — Production-Grade Backend Engineering

    Ownership boundary: This skill owns API design, app architecture, database optimization, error handling, middleware, queues, long-lived connections, and app-level observability/health hooks. Deployment strategy, rollback proof, rollout shape, SLOs, alert routing, incident response, and operational readiness gates are owned by dev-devops. Backend exposes the app-level hooks that DevOps operational gates consume.

    Build reliable, secure, and maintainable server-side applications. This skill is a routing role that activates by change-surface: whenever the work primarily touches APIs, servers, services, jobs, data access, schemas, migrations, or operational backend behavior, use this skill and then read the relevant references.

    C0/C1 work (small local patches): See dev §0.0 Work Classifier + §0.1 Patch Fast-Path before reading references.

    dev is canonical: dev §0.2 Rule Classes, §3 Verification Gate, and §5 Safety Rules apply to all work governed by this skill.

    Modular References

    FileWhen to ReadWhat It Covers
    references/core/crud-api.mdC2 ordinary CRUD/resource endpointsRoute/schema/service/query basics, five operations, error+permission mapping
    references/core/api-design.mdNew/changed API style, or C3+ API work (C2 ordinary slice: crud-api.md alone suffices)REST conventions, response envelopes, HTTP status, pagination, GraphQL, gRPC, tRPC
    references/core/api-lifecycle.mdAPI versioning, deprecation, migrationVersioning strategy, RFC 9745/8594 lifecycle, breaking-change gates
    references/core/architecture.mdNew features at C3+ (C2 ordinary slice: crud-api.md alone suffices)Layered architecture, DDD, SOLID, when to split, monolith vs micro
    references/core/anti-slop-backend.mdNew endpoints, classes, or modulesBanned patterns: god classes, raw SQL in services, magic numbers, etc.
    references/core/observability.mdProduction deploymentsOpenTelemetry, structured logging, distributed tracing, alerting
    references/core/health-checks.mdProduction/long-lived servicesLiveness, readiness, startup probes, dependency checks
    references/core/process-isolation.mdCPU-bound or untrusted workworker_threads vs child_process vs separate service, communication, resource limits
    references/core/caching.mdPerformance optimizationRedis patterns, CDN, connection pooling, cache invalidation
    references/stacks/node.mdNode.js/TypeScript projectsExpress/Fastify, middleware, Zod validation, ESM, error handling
    references/stacks/python.mdPython projectsFastAPI/Django, Pydantic, async patterns, testing
    references/stacks/database.mdDatabase design/optimizationPostgreSQL, MongoDB, indexing, N+1, migrations, ORM comparison
    references/core/ml-serving.mdML model deployment, GPU inferencevLLM/SGLang runtime selection, FastAPI+GPU patterns, dynamic batching, quantization
    references/core/llm-integration.mdRAG, LLM API integration, prompt engineeringChunking, hybrid search, vector DB, structured output, LangChain/LlamaIndex 2026
    references/core/mobile-api.mdMobile app API patternsBFF, push notifications, offline sync, mobile auth, API optimization

    Read api-design.md + anti-slop-backend.md first, then the relevant stack file. For C2 ordinary slices, crud-api.md alone suffices; read api-design.md/architecture.md for new API styles or C3+ work.

    When backend decisions depend on current external API docs, API lifecycle changes, LLM/RAG provider behavior, dependency freshness, or package/source evidence, read the active search skill and follow its query-rewrite, source-fetch, and evidence-status rules.


    0. Stack Detection & Architecture Clarification

    Auto-detect (existing projects)

    File FoundProject Type
    tsconfig.jsonTypeScript (Node)
    package.json (no ts)JavaScript (Node)
    pyproject.toml/requirements.txtPython
    go.modGo
    Cargo.tomlRust

    If config files exist → detect silently and proceed.

    Architecture Clarification (new or ambiguous projects)

    When the request has unspecified technology or unclear scope, clarify before coding:

    1. Identify what's ambiguous from this list:
    DimensionOptions to present
    API styleREST (default) · GraphQL (BFF/mobile) · gRPC (internal microservices) · tRPC (TS monorepo)
    DatabasePostgreSQL (default, ACID) · MongoDB (flexible schema) · SQLite (embedded)
    Auth methodJWT + refresh (stateless) · Session-based (simple) · OAuth 2.1 (3rd party)
    RealtimeNot needed (default) · WebSocket · SSE · Polling
    ArchitectureMonolith (default) · Modular monolith · Microservices
    1. Recommend one with reasoning: cite project context. e.g., "Small team → monolith + PostgreSQL + JWT is the simplest starting point."
    2. Over-engineering guard: A CRUD API probably doesn't need GraphQL + microservices + event sourcing. Simple → complex, not the reverse.
    3. One round limit: 2-3 options → recommend → confirm → proceed.

    If the user already specifies clear tech (e.g. "FastAPI로 REST API 만들어줘"), skip this entirely.

    Node/framework defaults (verified 2026-07-02): production uses Active/Maintenance LTS — Node 24 (Active) for new services. Framework: Fastify for greenfield Node APIs; Express 5 for legacy/ecosystem compatibility; Hono for edge/serverless/multi-runtime Web-Standards APIs. New TS validation baseline: Zod v4 (read the migration guide before upgrading v3 projects).

    For new Node backend source files, prefer .ts when the repo supports TypeScript or is greenfield. Inherit dev TypeScript strict-compatibility rules. If backend boundaries are unclear, read existing source-of-truth docs/logs first, then document routes, services, repositories, data stores, and runtime commands in the repo's existing SOT before broad implementation.


    1. Architecture Decision

    Before coding, identify the right pattern:

    Team SizeDefault Starting Point
    1-3 devsModular monolith
    4-10 devsModular monolith or SOA
    10+ devsConsider microservices

    Default to monolith. Extract only when you have a proven need (different scaling, independent deployment, technology mismatch).

    See references/core/architecture.md for full decision matrices.

    API Protocol Decision

    ProtocolChoose WhenAvoid When
    RESTPublic/partner APIs, simple CRUD, caching mattersClients need flexible data shapes
    GraphQLMobile/BFF, multiple resources per request, bandwidth-constrainedSimple CRUD, server-to-server, file uploads
    gRPCInternal microservices, high-perf binary, bidirectional streamingBrowser clients (without gRPC-Web), public APIs
    tRPCTypeScript monorepo, internal tools, rapid prototypingPolyglot environments, public APIs

    Hybrid pattern (verified 2026-07-02 — OpenAPI 3.1+, prefer 3.2 where tooling supports; tRPC v11; Apollo Federation ONLY for multi-subgraph supergraphs):

    Public/Partner → REST (OpenAPI 3.1)
    Mobile/Web BFF → GraphQL (Apollo Federation)
    Internal services → gRPC (Protobuf contracts)
    TS internal tools → tRPC (zero-codegen type safety)
    

    See references/core/api-design.md for protocol-specific patterns.

    Long-Lived Connection Operation

    Rules for SSE, WebSocket, and any connection held open beyond a single request-response cycle.

    Lifecycle Rules:

    ParameterDefaultRationale
    Heartbeat interval15-30sDetect dead connections before TCP timeout (varies by proxy)
    Reconnection backoffExponential 1s-30s with jitterPrevent thundering herd on server restart
    Max connection duration1h (SSE), 24h (WebSocket)Force reconnect to rebalance and prevent memory leaks
    Connections per clientCap at 6 (SSE) or 1-2 (WebSocket)Browser limits + server memory budget

    Server-Side Requirements:

    • Connection registry: Track all active connections in-memory (Map by client/session ID). Required for graceful drain and debugging.
    • Graceful drain on deploy: Stop accepting new connections → send "reconnect" frame to existing → wait drain timeout → close.
    • Memory budget: Allocate max memory per connection (e.g., 2KB buffer). Monitor total; reject new connections when approaching limit.
    • Backpressure: If client stops consuming, buffer up to N messages then drop oldest or disconnect.

    Pattern — "202 + Job ID" for Long Operations:

    Instead of holding a connection open for a slow operation:

    POST /generate → 202 { jobId: "j_abc123" }
    GET /jobs/j_abc123 → { status: "processing", progress: 0.6 }
                       → { status: "complete", result: {...} }
    

    Use SSE/WebSocket only for push notifications about job status — not for the operation itself.

    Banned:

    BannedFix
    Unbounded connections (no cap, no registry)Connection registry + cap per client + global max
    No heartbeat (rely on TCP keepalive only)Application-level heartbeat every 15-30s
    Blocking event loop per connection (sync work in message handler)Offload to worker thread or queue; handler stays async
    Holding connection open for >5s synchronous workReturn 202 + job ID; notify via push when done
    No reconnection logic on client sideImplement exponential backoff with jitter

    Server Runtime Safety (DEFAULT)

    Rule (BACKEND-RUNTIME-01): Production server runtimes set explicit read, write, request/idle, and graceful-shutdown timeouts; drain on SIGTERM/deploy by stopping new accepts, letting in-flight work finish within the shutdown budget, then closing; and propagate the request ID from ingress into structured logs, traces, queued work, and outbound calls where the stack supports it.


    2. Layered Architecture (Default; Allow Serverless Handlers, Vertical Slices, and Small Scripts When Appropriate)

    Routes → Controllers → Services → Repositories → Database
      │          │             │            │
      │          │             │            └── Data access only
      │          │             └── Business logic (validation at controller boundary — service trusts caller per dev-architecture §4)
      │          └── Parse HTTP, format response
      └── URL mapping, middleware
    

    Rules:

    • Routes: URL patterns + middleware only. No logic.
    • Controllers: parse input, call services, format output. No business rules.
    • Services: receive/return plain data (not req/res). All logic here.
    • Repositories: abstract DB access. Services access data through repositories only.

    Boundary Parsing Contract (DEFAULT)

    Rule (BACKEND-BOUNDARY-01): Parse once at ingress/trust boundaries; inside that boundary, typed values are proof. Do not duplicate schema validation, null defense, or defensive parsing in services unless data crosses a new trust boundary. Canonical boundary-defense ownership stays in dev-architecture §4; this is the backend stub.

    Repository Pattern (Interface Abstraction)

    Use repository interfaces so services depend on abstractions, enabling mocking and swapping implementations.

    Async Task Queue Patterns

    When work exceeds what an HTTP response cycle should hold open, use a queue.

    Decision: Queue vs Direct:

    ConditionUse QueueUse Direct
    Execution time >5sYesNo
    Must be retryable on failureYesNo
    Fire-and-forget (caller doesn't wait)YesNo
    <1s, idempotent, caller needs immediate resultNoYes
    Real-time user-facing validationNoYes

    Pattern — Accept, Queue, Notify:

    1. Client  → POST /tasks       → Server validates, enqueues
    2. Server  → 202 { jobId }     → Client receives immediately
    3. Worker  → picks from queue  → executes task
    4. Client  → GET /tasks/{id}   → polls status (or receives webhook/SSE push)
    5. Worker  → completes         → writes result, triggers notification
    

    Queue Selection Guide:

    QueueWhenNotes
    BullMQ (Redis)Node.js, need retries + priorities + rate limitingMost mature Node queue; requires Redis
    Celery (Redis/RabbitMQ)Python, distributed workers, periodic tasksDe facto Python standard
    pg-boss (PostgreSQL)Node.js, already have Postgres, moderate scaleNo extra infra; SKIP_LOCKED-based
    Simple DB queue (polling)Small scale (<100 jobs/min), any languagestatus column + SELECT FOR UPDATE SKIP LOCKED
    SQS / Cloud TasksServerless, managed, very high scaleNo infra to manage; at-least-once delivery
    TemporalDurable multi-step workflows: sagas, human-in-loop, long-running AI/business processesWorkflow engine, NOT a default queue replacement

    Required Safeguards:

    SafeguardRule
    Idempotency keyEvery enqueue call must include a unique idempotency key; dedup on insert
    Dead letter queue (DLQ)Failed 3x (configurable) → move to DLQ → alert → manual review
    Max retriesSet explicit limit (default: 3); exponential backoff between attempts
    Timeout per jobEvery job has a max execution time; kill and retry on exceed
    Visibility timeoutLock duration > expected execution time; prevent duplicate processing
    ObservabilityEmit metrics: queue depth, processing time p95, DLQ size, failure rate

    Banned:

    BannedFix
    Synchronous long operation blocking HTTP response (>5s)Enqueue + return 202 + job ID
    Queue without DLQAlways configure DLQ; alert on DLQ depth > 0
    Infinite retries (no max)Set maxRetries=3 with exponential backoff
    No idempotency (duplicate jobs on retry)Idempotency key on every enqueue; dedup in worker
    No timeout on job executionSet per-job timeout; kill + mark failed on exceed
    Polling without backoff (tight loop)Poll with interval (1-5s) or use blocking pop / push notification

    3. Error Handling

    TypeHTTPLog Level
    Validation400warn
    Authentication401warn
    Authorization403warn
    Not found404info
    Conflict409warn
    Rate limit429info
    Internal error500error + stack

    Use a centralized AppError class (DEFAULT — when the repo already has an error convention, follow it instead). Distinguish operational vs programmer errors.

    Error Taxonomy (AppError Hierarchy)

    Create an AppError base class with statusCode, code, and isOperational properties. Extend for each error type (ValidationError, NotFoundError, etc.).

    Result Pattern (conditional)

    Consider the Result/Either pattern (e.g. neverthrow) for recoverable domain errors where explicit error handling improves clarity — adopt it only when the project scope justifies it and the repo doesn't already settle error style (HEURISTIC, not a universal requirement).

    LibraryWhen to Use
    neverthrowDefault choice — small explicit Result<T, E> for recoverable domain errors
    EffectOnly when the app benefits from a full effect runtime: typed errors, retries, resources, concurrency, tracing

    Rule: Use Result where recoverable/domain errors are first-class. Reserve try/catch for error boundaries (middleware, top-level handlers) only.


    4. Middleware Execution Order

    Apply in this sequence (order matters):

    1. Request ID generation
    2. Request logging
    3. Security headers (CORS, CSP, HSTS)
    4. Rate limiting
    5. Authentication
    6. Authorization
    7. Body parsing
    8. Input validation (schema)
    9. Route handler
    10. Error handler
    11. Response logging

    5. API Response Contract

    API endpoints should use a stable response envelope (DEFAULT) unless the protocol (GraphQL, gRPC, SSE) defines its own or the repo already has a different established contract — follow the existing contract first. Envelope, OTel, health checks, and deployment-readiness checks are production-surface concerns (dev §0.4 shared definition), conditional by project scope, not universal blockers.

    Rules:

    • success boolean at top level — never infer from HTTP status alone
    • error.code is machine-readable (UPPER_SNAKE), error.message is human-readable
    • meta.requestId on every response — enables cross-service tracing
    • Pagination uses cursor-based (after/before) for large datasets, offset-based (page/pageSize) for admin UIs
    • Nullability: prefer consistent key presence; omit when sparse payloads are intentional
    • Timestamps: ISO 8601 UTC (2024-01-15T09:30:00Z), never Unix epoch in JSON
    • Money: integer cents + currency code, never floating point

    See references/core/api-design.md for protocol-specific patterns (REST, GraphQL, gRPC, tRPC).


    6. Caching Strategy

    Decision rules:

    • Say Redis-compatible, not Redis-only (verified 2026-07-02): prefer Valkey (Linux Foundation, BSD) for permissive OSS/self-hosted defaults; choose Redis when managed-service, module, or license posture justifies it.
    • Cache only after correctness is proven on the uncached path.
    • Prefer cache-aside by default; use write-through only when strong consistency matters.
    • Every key has a namespace, version, stable identifier, TTL, and invalidation trigger.
    • Never cache error responses or personalized CDN responses; protect cached PII with encryption and access controls.
    • Add stampede protection for hot keys and monitor hit rate, pool exhaustion, and stale-read incidents.

    See references/core/caching.md for TTL guidance, Redis patterns, CDN rules, invalidation triggers, connection pooling, and code examples.


    7. Observability (OpenTelemetry)

    Decision rules:

    • OTel maturity (verified 2026-07-02): traces/metrics are Stable in JS/Python; logs are still Development — baseline is trace/span-correlated structured logs + OTel traces/metrics.
    • Production services emit traces, metrics, and structured JSON logs with requestId, traceId, and spanId.
    • Start with OTel auto-instrumentation, then add custom spans only for business-critical or non-instrumented work.
    • Never log PII, secrets, full request/response bodies, or noisy stack traces outside error boundaries.
    • Page only on customer-impacting signals tied to SLOs; use warning alerts for capacity trends.

    See references/core/observability.md for OTel setup, structured logging conventions, trace propagation, dashboards, RUM correlation, and alerting guidance.


    8. Skeleton Project Evaluation

    When starting from a template or boilerplate, verify before building on top:

    CheckWhat to Verify
    DependenciesUp-to-date? CVEs? Unnecessary packages?
    Architecture fitDoes the template's structure match your actual needs?
    Auth/securityIs the auth pattern appropriate for your use case?
    DatabaseIs the ORM/query builder suitable for your data model?
    Dead codeRemove unused example routes, models, and middleware
    Config managementEnvironment-based config, no hardcoded values

    Treat templates as starting points, not gospel. Strip to essentials, then add what you need.


    9. API Performance Targets (HEURISTIC defaults — define product SLOs from user journeys and alert on error-budget burn, not raw percentiles alone)

    MetricTargetEscalation
    p50 response time (reads)≤ 50msProfile with tracing
    p95 response time (reads)≤ 200ms target, alert at >500ms (see observability.md)Optimization target
    p95 response time (writes)≤ 500msAcceptable for complex writes
    p99 response time≤ 1000msInvestigate outliers
    Error rate< 0.1% target, alert at >1% (see observability.md)Optimization target
    • Measure at the handler level, not including network
    • Use Server-Timing header to expose backend timing to frontend
    • Log slow queries (> 100ms) with EXPLAIN output
    • Connection pool (long-running servers): min = CPU cores, max = CPU cores × 4; for serverless/Lambda use min = 0–2

    API responses that drive UI must include descriptive error messages (not just codes) for screen reader announcement, pagination metadata (total count) for assistive technology, and Content-Language header matching response body language.

    10. SEO Support Endpoints

    When the app serves web pages (SSR/SSG):

    • GET /sitemap.xml — dynamic sitemap generation with <lastmod>
    • GET /robots.txt — configurable per-environment (disallow staging/preview)
    • Structured data: provide JSON-LD data in API responses when frontend needs it
    • Redirect chains: max 1 hop (301 for permanent, 308 for POST-preserving)

    11. Deployment Handoff

    Deployment strategy, rollout shape, rollback proof, and feature-flag rollout policy are owned by dev-devops. Backend owns the app compatibility hooks that make safe deployment possible:

    • Database migrations: backward-compatible (expand-then-contract), separated from code deploy
    • Feature-flag checks in application code (rollout policy lives in dev-devops)
    • Health/readiness endpoint behavior when requested by the deployment surface
    • Graceful-shutdown hooks for drain sequencing
    • Analytical data / ETL / pipeline quality: load dev-data.
    • API consumer context / frontend contract alignment: load dev-frontend.
    • Test strategy / verification harnesses / QA execution: load dev-testing.
    • Backend failure RCA methodology: load dev-debugging.
    • New project setup / file placement conventions: load dev-scaffolding.

    12. Pre-Flight Checklist

    Before delivering:

    • Consistent response envelope on every endpoint
    • Input validation with schema (Zod, Pydantic, etc.)
    • Authentication middleware on protected routes
    • Rate limiting on public endpoints
    • Structured JSON logging with requestId and traceId
    • Error handler returns proper HTTP codes via AppError hierarchy
    • No raw SQL in service layer
    • No hardcoded secrets
    • Migration code is backward-compatible when release sequencing requires it
    • Observability: traces and structured logs wired (see references/core/observability.md)
    • Health/readiness handlers exist when the runtime/deploy surface requires them; operational gates live in dev-devops
    • API performance: p95 reads ≤ 200ms, slow queries logged with EXPLAIN (§9)
    • SEO endpoints: sitemap.xml + robots.txt if serving web pages (§10)
    • Security review: delegate to dev-security/SKILL.md for production readiness
    • Stack-specific rules followed (see references/stacks/)

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