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CodeAssist
CodeAssist には liauw-media から収集した 59 個の skills があり、リポジトリ単位の職業カバレッジとサイト内 skill 詳細ページを表示します。
このリポジトリの skills
Build immersive, scroll-driven websites with GSAP ScrollTrigger, Lenis smooth scroll, parallax effects, and cinematic page transitions. Use when building premium corporate sites, landing pages, or marketing microsites that need motion and polish beyond static designs.
Use when adding docstrings, creating API documentation, or building documentation sites. Invoke for OpenAPI/Swagger specs, JSDoc, doc portals, tutorials, user guides.
Use when reviewing pull requests, conducting code quality audits, or identifying security vulnerabilities. Invoke for PR reviews, code quality checks, refactoring suggestions.
Use when investigating slow queries, analyzing execution plans, or optimizing database performance. Invoke for index design, query rewrites, configuration tuning, partitioning strategies, lock contention resolution.
Use when investigating errors, analyzing stack traces, or finding root causes of unexpected behavior. Invoke for error investigation, troubleshooting, log analysis, root cause analysis.
Use when setting up CI/CD pipelines, containerizing applications, or managing infrastructure as code. Invoke for pipelines, Docker, Kubernetes, cloud platforms, GitOps.
Use when building Laravel 10+ applications requiring Eloquent ORM, API resources, or queue systems. Invoke for Laravel models, Livewire components, Sanctum authentication, Horizon queues.
Use when building TypeScript applications requiring advanced type systems, generics, or full-stack type safety. Invoke for type guards, utility types, tRPC integration, monorepo setup.
Alibaba Cloud architecture patterns and best practices. Use when designing, deploying, or reviewing infrastructure on Alibaba Cloud including ECS, ACK, Function Compute, and OSS.
AWS cloud architecture patterns and best practices. Use when designing, deploying, or reviewing AWS infrastructure including EC2, ECS, EKS, Lambda, RDS, S3, IAM, and VPC.
Microsoft Azure architecture patterns and best practices. Use when designing, deploying, or reviewing Azure infrastructure including AKS, App Service, Functions, CosmosDB, and Entra ID.
Google Cloud Platform architecture patterns and best practices. Use when designing, deploying, or reviewing GCP infrastructure including GKE, Cloud Run, Cloud Functions, BigQuery, and IAM.
Vercel deployment patterns and best practices. Use when deploying frontend applications, configuring edge functions, setting up preview deployments, or optimizing Next.js applications.
Configuration management with Ansible. Use when automating server setup, application deployment, orchestrating multi-server tasks, or managing infrastructure configuration.
Docker containerization best practices. Use when building Docker images, writing Dockerfiles, configuring Docker Compose, or troubleshooting container issues.
Kubernetes container orchestration. Use when deploying to Kubernetes, writing manifests, configuring Helm charts, or troubleshooting cluster issues.
Infrastructure as Code with Terraform. Use when provisioning cloud resources, managing state, creating modules, or reviewing Terraform configurations.
Cloud cost optimization and FinOps practices. Use when analyzing cloud costs, implementing savings strategies, or optimizing resource usage.
Cloud monitoring with Prometheus, Grafana, and cloud-native tools. Use when setting up metrics, alerts, dashboards, or troubleshooting performance issues.
GitOps deployment patterns with ArgoCD and Flux. Use when implementing Git-based infrastructure management, continuous deployment, or declarative operations.
Policy as Code with OPA, Kyverno, and Checkov. Use when implementing governance, compliance automation, or security policies for infrastructure and Kubernetes.
Use when building AI agent systems. Covers agent loops, tool calling, planning patterns, memory systems, multi-agent coordination, and safety guardrails. Apply when creating autonomous AI workflows, coding assistants, or task automation systems.
Use when integrating LLM APIs into applications. Covers API patterns, prompt templates, streaming, error handling, cost optimization, and provider abstraction. Apply when building chat interfaces, completion endpoints, or AI-powered features.
Use when working on long-running projects or needing context across sessions. Covers memory architecture, privacy controls, efficient retrieval, and integration with claude-mem plugin. Apply when building features that span multiple sessions or need historical context.
Use when building retrieval-augmented generation systems. Covers chunking strategies, embedding models, vector databases, retrieval patterns, and hybrid search. Apply when adding knowledge bases, document Q&A, or semantic search to applications.
Enforce one branch per issue, small focused commits, and clean git history. Use with /branch command.
Use when performing security audits or system hardening. Teaches security assessment principles and prioritization.
Use when setting up CI/CD pipelines. Teaches pipeline design principles and references platform-specific templates.
Self-review before declaring work complete
Backup database before tests, migrations, or other database operations
Check for relevant skills before starting any task
Delegate tasks to remote Claude Code agent containers for parallel execution, long-running analysis, or resource-intensive operations.
Establish or analyze brand identity guidelines. Creates comprehensive brand documentation that frontend-design, testing, and other skills automatically reference for consistent execution.
Create distinctive, production-grade frontend interfaces with high design quality. Use when building web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
Use when testing frontend applications. AI-assisted browser testing with Playwright MCP. Fast, deterministic, no vision models needed.
Use when debugging web applications or automating browser tasks. Leverage Chrome DevTools MCP for inspection, performance analysis, and automated testing.
Use when optimizing website performance. Run Google Lighthouse audits via MCP to measure metrics, identify bottlenecks, and iterate on improvements.
MANDATORY: Use gh (GitHub) or glab (GitLab) CLI for ALL issue/task management. Unified workflow across platforms.
Use when finishing any task. Final checklist before marking complete. Ensures nothing forgotten, all tests pass, documentation updated.
MANDATORY setup for all projects. Automated code quality enforcement before commits. Prevents bad code from entering repository.