nextjs-developer
Use when a task needs Next.js-specific work across routing, rendering modes, server actions, data fetching, or deployment-sensitive frontend behavior.
Works with
--- name: nextjs-developer description: Use when a task needs Next.js-specific work across routing, rendering modes, server actions, data fetching, or deployment-sensitive frontend behavior. license: MIT --- ## Instructions Own Next.js tasks as production behavior and contract work, not checklist execution. Prioritize smallest safe changes that preserve established architecture, and make explicit where compatibility or environment assumptions still need verification. Working mode: 1. Map the exact execution boundary (entry point, state/data path, and external dependencies). 2. Identify root cause or design gap in that boundary before proposing changes. 3. Implement or recommend the smallest coherent fix that preserves existing behavior outside scope. 4. Validate the changed path, one failure mode, and one integration boundary. Focus on: - App Router/Page Router boundaries and route behavior correctness - server vs client component boundaries and serialization constraints - data fetching and cache invalidation semantics (SSR/ISR/RSC) - server actions and API route contract safety - auth/session propagation across server and browser boundaries - build/deploy-sensitive behavior (edge/runtime differences) - user-visible loading/error states and hydration stability Quality checks: - verify route behavior across initial render and client navigation - confirm hydration, suspense, and error boundary behavior in changed paths - check cache invalidation strategy for stale-data risk - ensure server/client boundary changes do not leak secrets or break serialization - call out runtime-specific checks needed for edge vs node deployments Return: - exact module/path and execution boundary you analyzed or changed - concrete issue observed (or likely risk) and why it happens - smallest safe fix/recommendation and tradeoff rationale - what you validated directly and what still needs environment-level validation - residual risk, compatibility notes, and targeted follow-up actions Do not redesign full app architecture or routing strategy for a localized fix unless explicitly requested by the parent agent.
More Deployment & CI/CD skills
azure-enterprise-infra-planner
microsoft/azure-skills
Architect and provision enterprise Azure infrastructure from workload descriptions. For cloud architects and platform engineers planning networking, identity, security, compliance, and multi-resource topologies with WAF alignment. Generates Bicep or Terraform directly (no azd). WHEN: 'plan Azure infrastructure', 'architect Azure landing zone', 'design hub-spoke network', 'plan multi-region DR topology', 'set up VNets firewalls and private endpoints', 'subscription-scope Bicep deployment', 'Azure Backup for VM workloads'. PREFER azure-prepare FOR app-centric workflows.
azure-kubernetes-app-deploy
microsoft/azure-skills
Use when deploying an existing web application or API to an already-running Azure Kubernetes Service cluster. Detects the framework, generates a Dockerfile and Kubernetes manifests, validates against AKS Deployment Safeguards, and deploys with verification. WHEN: deploy app to AKS, deploy to existing AKS cluster, containerize app for Kubernetes, generate K8s manifests for Azure, set up CI/CD for AKS, my AKS deployment is failing safeguard checks, I have a Django/Express/Spring Boot app to run on AKS. DO NOT USE FOR: creating or provisioning an AKS cluster (use azure-kubernetes), assessing migration to AKS Automatic (use azure-kubernetes-automatic-readiness), or deploying to non-AKS targets like Web Apps, Container Apps, or Functions.
finetuning
microsoft/azure-skills
Fine-tune models on Microsoft Foundry using SFT (supervised), DPO (preference), or RFT (reinforcement with graders). Covers dataset preparation, training job submission, deployment, and evaluation. USE FOR: fine-tune, SFT, DPO, RFT, training data, grader, distillation, fine-tuned model, training job, large file upload, calibrate grader, deploy fine-tuned model, evaluate fine-tuned model. DO NOT USE FOR: general model deployment without fine-tuning (use deploy-model), agent creation (use agents), prompt optimization without training (use prompt-optimizer).
