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Implement a JSON-RPC 2.0 A2A server with full task lifecycle management (submitted/working/completed/failed/canceled/input-required), SSE streaming, and push notifications. Use when implementing an agent that participates in multi-agent A2A workflows, building a backend for an Agent Card, adding A2A protocol support to an existing agent or service, or deploying an agent that must interoperate with other A2A-compliant agents.

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Implement audit trail functionality for R projects in regulated environments. Covers logging, provenance tracking, electronic signatures, data integrity checks, and 21 CFR Part 11 compliance. Use when an R analysis requires electronic records compliance (21 CFR Part 11), when you need to track who did what and when in an analysis, when implementing data provenance tracking, or when creating tamper-evident analysis logs for regulatory submissions.

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 a generative diffusion model (DDPM or score-based) with noise scheduling, U-Net architecture, training loop, and sampling procedures including DDIM acceleration. Use when building a generative model for image, audio, or molecular synthesis; implementing DDPM from a research paper; adding a custom noise schedule or conditioning mechanism; replacing a GAN-based generator with a diffusion alternative; or prototyping before scaling with production frameworks like diffusers.

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 electronic signatures compliant with 21 CFR Part 11 Subpart C and EU Annex 11. Covers signature manifestation (signer, date/time, meaning), signature-to-record binding, biometric vs non-biometric controls, policy creation, and user certification requirements. Use when a computerized system requires legally binding electronic signatures for GxP records, when replacing wet-ink signatures in regulated workflows, when implementing batch release or document approval workflows, or when a regulatory gap reveals missing signature controls.

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 GitOps continuous delivery using Argo CD or Flux with app-of-apps pattern, automated sync policies, drift detection, and multi-environment promotion. Manage Kubernetes deployments declaratively from Git with automated reconciliation. Use when implementing declarative infrastructure management, migrating from imperative kubectl commands to Git-driven deployments, setting up multi-environment promotion workflows, enforcing code review gates for production, or meeting audit and compliance requirements.

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。

Set up systematic data labeling workflows using Label Studio or similar tools. Implement quality controls, measure inter-annotator agreement, manage labeler teams, and integrate labeled data into ML training pipelines. Use when starting a supervised ML project that requires labeled training data, when model performance is limited by insufficient labeled examples, when labeling text, images, audio, or video, or when implementing active learning to prioritize the most valuable examples.

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 pharmaceutical serialisation and track-and-trace systems compliant with EU FMD, US DSCSA, and other global regulations. Covers unique identifier generation, aggregation hierarchy, EPCIS data exchange, and verification endpoint integration. Use when implementing serialisation for a new product launch, integrating with the EMVS/NMVS, designing DSCSA-compliant transaction exchange, building an EPCIS event repository, or extending serialisation to additional markets (China, Brazil, Russia).

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Deploy applications to Kubernetes clusters using kubectl manifests for Deployments, Services, ConfigMaps, Secrets, and Ingress resources. Implement health checks, resource limits, rolling updates, and Helm chart packaging for production deployments. Use when deploying new applications to EKS, GKE, AKS, or self-hosted clusters, migrating from Docker Compose to container orchestration, implementing zero-downtime rolling updates, or setting up multi-environment deployments across dev, staging, and production.

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 Service Level Objectives (SLO), Service Level Indicators (SLI), and Service Level Agreements (SLA) with error budget tracking, burn rate alerts, and automated reporting using Prometheus and tools like Sloth or Pyrra. Use when defining reliability targets for customer-facing services, balancing feature velocity against system reliability through error budgets, migrating from arbitrary uptime goals to data-driven metrics, or implementing Site Reliability Engineering practices.

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Deploy machine learning models to production serving infrastructure using MLflow, BentoML, or Seldon Core with REST/gRPC endpoints, implement autoscaling, monitoring, and A/B testing capabilities for high-performance model inference at scale. Use when deploying trained models for real-time inference, setting up REST or gRPC prediction APIs, implementing autoscaling for variable load, running A/B tests between model versions, or migrating from batch to real-time inference.

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Unify metrics, logs, and traces for cohesive debugging. Implement exemplars for log-to-trace linking, build unified dashboards using RED/USE methods, and enable rapid root cause analysis across observability signals. Use when investigating complex incidents spanning multiple systems, reducing mean time to resolution, implementing distributed tracing, or moving from siloed tools to a unified observability platform.

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Set up centralized log aggregation with Loki and Promtail (or ELK stack), including log parsing, label extraction, retention policies, and integration with metrics for correlation. Use when consolidating logs from multiple services into a searchable system, replacing local log files with centralized queryable storage, correlating logs with metrics and traces, implementing structured logging with label extraction, or troubleshooting production incidents requiring cross-service log analysis.

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Author a new agent-almanac workflow — a self-contained `.mjs` orchestration script run by Claude Code's Workflow tool. Covers choosing a workflow over a team, copying the template, the triple-name discovery contract, the pure-literal meta and sidecar frontmatter, building the body with the injected primitives, the advisory/implementing capability contract, the adversarial-verification fail-safes, validation, and manual installation. Use when you have a repeatable, parameterized procedure that coordinates several agents and want it captured as a reusable, auditable artifact whose control flow is fixed in code.

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Deploy and configure an API gateway (Kong or Traefik) to handle API traffic management, authentication, rate limiting, request/response transformation, and routing. Covers plugin configuration, upstream services, consumer management, and integration with existing infrastructure. Use when multiple backend services need a unified API endpoint, when centralized authentication or rate limiting is required, when implementing API versioning, or when needing detailed analytics and load balancing for microservices.

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Configure Prometheus Alertmanager with routing trees, receivers (Slack, PagerDuty, email), inhibition rules, silences, and notification templates for actionable incident alerting. Use when implementing proactive monitoring with automated incident detection, routing alerts to the appropriate team by severity, reducing alert fatigue through grouping and deduplication, integrating with on-call systems like PagerDuty, or migrating from legacy alerting to Prometheus-based alerting.

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Configure Kubernetes Ingress networking with NGINX Ingress Controller, cert-manager for automated TLS certificate management, path-based routing, rate limiting, and multi-domain hosting with SSL termination and load balancing. Use when exposing multiple Kubernetes services via a single load balancer, implementing path-based or host-based routing, automating TLS certificate issuance with Let's Encrypt, or setting up blue-green and canary deployments with traffic splitting.

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 multi-stage CI/CD pipelines using GitHub Actions with matrix builds, dependency caching, artifact management, and secret handling. Create workflows that span linting, testing, building, and deployment stages with parallel execution and conditional logic. Use when setting up automated testing and deployment for a new project, migrating from Jenkins or CircleCI to GitHub Actions, implementing matrix builds across platforms, adding build caching, or creating multi-stage pipelines with security scanning and quality gates.

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。

Add Rcpp or RcppArmadillo integration to an R package for high-performance C++ code. Covers setup, writing C++ functions, RcppExports generation, testing compiled code, and debugging. Use when an R function is too slow and profiling confirms a bottleneck, when you need to interface with existing C/C++ libraries, or when implementing algorithms (loops, recursion, linear algebra) that benefit from compiled code.

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Build a plugin or adapter for a CLI tool using the abstract base class pattern. Covers defining the contract (static fields, required methods), choosing an installation strategy (symlink, copy, append-to-file), implementing detection, install/uninstall with idempotency, listing, auditing, and registering the plugin. Use when adding support for a new framework to a CLI installer, building a plugin system for any multi-target tool, or extending an existing adapter architecture.

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。

Next.js project structure, App Router conventions, file-based routing primitives, layouts, error boundaries, metadata, image and font optimization, configuration. Apply when implementing or modifying Next.js features. Use this skill to: - Pick the correct file convention (page/layout/loading/error/not-found/route/template/default). - Structure a feature within the App Router tree. - Set up metadata for SEO and OpenGraph. - Configure next.config.js for headers, redirects, image domains. - Use built-in fonts and images correctly. Do NOT use this skill for: - Server vs Client component boundaries (see server-component-patterns). - Data fetching patterns (see nextjs-data-fetching). - Complex routing (parallel/intercepting routes — see nextjs-routing). - Testing (see nextjs-testing).

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。

NestJS module structure, dependency injection, lifecycle, configuration, exception handling, and logging conventions. Apply when implementing or modifying NestJS backend code. Use this skill to: - Structure feature modules (one feature = one module). - Wire DI correctly (constructor injection, scopes, custom tokens). - Set up ConfigModule, ValidationPipe, exception filters in main.ts. - Use lifecycle hooks for init and graceful shutdown. - Pick the right exception class for each error case. Do NOT use this skill for: - Decorator-specific patterns (see decorator-patterns). - ORM/data access (see nest-data-layer). - GraphQL/WebSockets/Microservices (see nest-advanced). - Testing (see nest-testing).

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React component structure, hooks rules, file naming, project layout, composition patterns, performance idioms, and effects discipline. Apply when implementing or modifying React SPA code. Use this skill to: - Structure a new component or feature folder. - Apply hooks correctly (rules, naming, dependency arrays). - Compose components via children, render props, or compound patterns. - Write effects only when needed (and avoid common misuses). - Pick performance escape hatches (memo, useMemo, useCallback) when justified. Do NOT use this skill for: - State management lib choice (see react-state-management). - Routing primitives (see react-routing). - Form patterns (see react-forms). - Testing (see react-testing).

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。

Node.js backend conventions: project layout, configuration, logging, routing, and error handling patterns. Apply when implementing or modifying Node.js backend code in projects matching the nodejs stack profile. Use this skill to: - Pick conventional file/folder structure for a new module. - Wire configuration through env vars correctly. - Use the project's existing logger style. - Implement error handling that matches the framework (Express/Fastify/Koa). - Follow async/await patterns consistently. Do NOT use this skill for: - Frontend code (React/Vue/RN have their own conventions). - NestJS-specific patterns (decorators, DI, modules) — nest-plugin owns those. - Database schema design (call out as a sub-task; npm-patterns covers package management, not DB).

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Use when implementing pool/slab/arena allocators, tuning jemalloc/mimalloc/tcmalloc, writing a Rust GlobalAlloc, or benchmarking allocator performance and fragmentation.

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。