Verify Open Claude Code package integrity, release tests, and automation evidence. Use when asked whether an OCC release is published, tested, or fully automated.
日本語の概要は準備中です。原文の説明を表示しています。
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概要と使いどころ
Verify Open Claude Code package integrity, release tests, and automation evidence. Use when asked whether an OCC release is published, tested, or fully automated.
日本語の概要は準備中です。原文の説明を表示しています。
Design and implement Internal Developer Platforms (IDPs) with self-service capabilities, golden paths, and developer experience optimization. Covers platform strategy, IDP architecture (Backstage, Port), infrastructure orchestration (Crossplane), GitOps (Argo CD), and adoption patterns. Use when building developer platforms, improving DevEx, or establishing platform teams.
日本語の概要は準備中です。原文の説明を表示しています。
Builds dashboards, reports, and data-driven interfaces requiring charts, graphs, or visual analytics. Provides systematic framework for selecting appropriate visualizations based on data characteristics and analytical purpose. Includes 24+ visualization types organized by purpose (trends, comparisons, distributions, relationships, flows, hierarchies, geospatial), accessibility patterns (WCAG 2.1 AA compliance), colorblind-safe palettes, and performance optimization strategies. Use when creating visualizations, choosing chart types, displaying data graphically, or designing data interfaces.
日本語の概要は準備中です。原文の説明を表示しています。
When validating system performance under load, identifying bottlenecks through profiling, or optimizing application responsiveness. Covers load testing (k6, Locust), profiling (CPU, memory, I/O), and optimization strategies (caching, query optimization, Core Web Vitals). Use for capacity planning, regression detection, and establishing performance SLOs.
日本語の概要は準備中です。原文の説明を表示しています。
Managing cloud infrastructure using declarative and imperative IaC tools. Use when provisioning cloud resources (Terraform/OpenTofu for multi-cloud, Pulumi for developer-centric workflows, AWS CDK for AWS-native infrastructure), designing reusable modules, implementing state management patterns, or establishing infrastructure deployment workflows.
日本語の概要は準備中です。原文の説明を表示しています。
API design and implementation across REST, GraphQL, gRPC, and tRPC patterns. Use when building backend services, public APIs, or service-to-service communication. Covers REST frameworks (FastAPI, Axum, Gin, Hono), GraphQL libraries (Strawberry, async-graphql, gqlgen, Pothos), gRPC (Tonic, Connect-Go), tRPC for TypeScript, pagination strategies (cursor-based, offset-based), rate limiting, caching, versioning, and OpenAPI documentation generation. Includes frontend integration patterns for forms, tables, dashboards, and ai-chat skills.
日本語の概要は準備中です。原文の説明を表示しています。
Design APIs that are secure, scalable, and maintainable using RESTful, GraphQL, and event-driven patterns. Use when designing new APIs, evolving existing APIs, or establishing API standards for teams.
日本語の概要は準備中です。原文の説明を表示しています。
Implementing multi-layer security scanning (container, SAST, DAST, SCA, secrets), SBOM generation, and risk-based vulnerability prioritization in CI/CD pipelines. Use when building DevSecOps workflows, ensuring compliance, or establishing security gates for container deployments.
日本語の概要は準備中です。原文の説明を表示しています。
Assembles component outputs from AI Design Components skills into unified, production-ready component systems with validated token integration, proper import chains, and framework-specific scaffolding. Use as the capstone skill after running theming, layout, dashboard, data-viz, or feedback skills to wire components into working React/Next.js, Python, or Rust projects.
日本語の概要は準備中です。原文の説明を表示しています。
Implement production-ready service mesh deployments with Istio, Linkerd, or Cilium. Configure mTLS, authorization policies, traffic routing, and progressive delivery patterns for secure, observable microservices. Use when setting up service-to-service communication, implementing zero-trust security, or enabling canary deployments.
日本語の概要は準備中です。原文の説明を表示しています。
Design comprehensive security architectures using defense-in-depth, zero trust principles, threat modeling (STRIDE, PASTA), and control frameworks (NIST CSF, CIS Controls, ISO 27001). Use when designing security for new systems, auditing existing architectures, or establishing security governance programs.
日本語の概要は準備中です。原文の説明を表示しています。
Design cloud network architectures with VPC patterns, subnet strategies, zero trust principles, and hybrid connectivity. Use when planning VPC topology, implementing multi-cloud networking, or establishing secure network segmentation for cloud workloads.
日本語の概要は準備中です。原文の説明を表示しています。
Strategic guidance for operationalizing machine learning models from experimentation to production. Covers experiment tracking (MLflow, Weights & Biases), model registry and versioning, feature stores (Feast, Tecton), model serving patterns (Seldon, KServe, BentoML), ML pipeline orchestration (Kubeflow, Airflow), and model monitoring (drift detection, observability). Use when designing ML infrastructure, selecting MLOps platforms, implementing continuous training pipelines, or establishing model governance.
日本語の概要は準備中です。原文の説明を表示しています。
Optimize cloud infrastructure costs through FinOps practices, commitment discounts, right-sizing, and automated cost management. Use when reducing cloud spend, implementing budget controls, or establishing cost visibility across AWS, Azure, GCP, and Kubernetes environments.
日本語の概要は準備中です。原文の説明を表示しています。
Scaffold a LaTeX project (`latex/main.tex`, optional bibliography wiring, structure) from an existing Markdown draft.
日本語の概要は準備中です。原文の説明を表示しています。
When the user wants to deeply understand their ideal customer before writing copy — pains, desires, inner monologue, and language. Also use when the user mentions "empathy engine", "know your target", "customer pain points", or asks to research their audience before writing Blitz Copy.
日本語の概要は準備中です。原文の説明を表示しています。
Assess tests for an identified code or test change, feature, PR or commit. USE FOR: review changed behavior or regression tests, prove pre-fix/missing behavior is detected, revision-bound red-green evidence. Polyglot. DO NOT USE without an identified change: hypothetical mutations or general suite blind spots (test-gap-analysis). Also exclude per-test readiness/A-F grades (grade-tests), coverage (coverage-analysis), new suites (code-testing), or mutation engines.
日本語の概要は準備中です。原文の説明を表示しています。
Build and debug Avalonia 11/12 .NET applications with XAML, compiled bindings, MVVM, custom controls, desktop lifetimes, and platform publishing. USE FOR: Avalonia projects, bindings, commands, themes, UI dispatch, trimming, or Native AOT. DO NOT USE FOR: WPF, WinUI, MAUI, Uno, or Avalonia XPF compatibility work. INVOKES: inspect installed versions, implement, and validate on the actual target platforms.
日本語の概要は準備中です。原文の説明を表示しています。
Create a persistent HeyGen avatar — a reusable face + voice identity for the agent, the user, or any named character — powered by HeyGen Avatar V technology. Prompt-based creation by default (description → HeyGen builds it); photo upload is optional for real-person digital twins. Use when: (1) giving the agent a face + voice so it can present videos ("bring yourself to life", "create your avatar", "give yourself an avatar", "design a presenter", "set up an avatar", "let's make an avatar"), (2) the user wants to appear in videos as themselves ("create my avatar", "I want my face in a video", "digital twin of me", "build me an avatar"), (3) building a named character presenter ("create an avatar called Cleo", "design a character named X"), (4) establishing HeyGen identity before making videos — the correct FIRST step when no avatar exists yet. Chain signal: when the user says both an identity/avatar action AND a video action in the same request ("create an avatar AND make a video", "set up identity THEN create a video", "design a presenter AND immediately record"), run heygen-avatar first, then heygen-video. Returns avatar_id + voice_id — pass directly to heygen-video to create HeyGen videos. NOT for: generating videos (use heygen-video), translating videos, or TTS-only tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Choosing an MSBuild CopyToOutputDirectory / CopyToPublishDirectory mode: Never, PreserveNewest, Always, and IfDifferent (MSBuild 17.13+), plus $(SkipUnchangedFilesOnCopyAlways). USE FOR: removing the per-build Always copy perf hit; resetting output files mutated between builds. DO NOT USE FOR: general incremental-build diagnosis (use incremental-build); non-MSBuild build systems.
日本語の概要は準備中です。原文の説明を表示しています。
Detects MSBuild projects with conflicting OutputPath or IntermediateOutputPath. USE FOR: builds failing with 'Cannot create a file when that file already exists', 'The process cannot access the file because it is being used by another process', intermittent build failures that succeed on retry, or missing/overwritten outputs in multi-project or multi-targeting builds where bin/obj (or project.assets.json) collide. Common causes: shared OutputPath, missing AppendTargetFrameworkToOutputPath, extra global properties (e.g. PublishReadyToRun), or SetTargetFramework on a ProjectReference to a single-targeting project. DO NOT USE FOR: file access errors unrelated to MSBuild (OS-level locking), single-project single-TFM builds, non-MSBuild build systems.
日本語の概要は準備中です。原文の説明を表示しています。
Establish MSBuild/.NET build performance baselines before optimizing. USE FOR: a .NET build or solution that is slow or has build-performance concerns; cold, warm, incremental, or no-op measurements; before/after comparisons; CI build output caching; static graph build decisions; artifacts output; and dependency graph trimming. Start here before build-perf-diagnostics, incremental-build, or build-parallelism. DO NOT USE for webpack, npm, JavaScript bundlers, or other non-MSBuild build systems. For detailed target/task/analyzer bottleneck analysis after baselining, use build-perf-diagnostics.
日本語の概要は準備中です。原文の説明を表示しています。
Configure and collect crash dumps for modern .NET applications. USE FOR: enabling automatic crash dumps for CoreCLR or NativeAOT, capturing dumps from running .NET processes, setting up dump collection in Docker or Kubernetes, using dotnet-dump collect or createdump. DO NOT USE FOR: analyzing or debugging dumps, post-mortem investigation with lldb/windbg/dotnet-dump analyze, profiling or tracing, or for .NET Framework processes.
日本語の概要は準備中です。原文の説明を表示しています。
Find caller-visible production changes existing tests would miss through pseudo-mutation analysis; verify candidates or close gaps only when requested. Includes read-only per-test composition for grading. Polyglot. USE FOR: would tests catch a bug, behavioral blind spots, surviving mutations. DO NOT USE FOR: concrete fix/feature revision proof (test-value-evidence); suite taxonomy (test-tagging); .NET coverage, Cobertura, plateaus or coverage-backed priorities (coverage-analysis); named CRAP (crap-score); new suites (code-testing); assertion/smell audits; mutation tools.
日本語の概要は準備中です。原文の説明を表示しています。