Skills directory · page 35

複数のストレージレイヤー（ローカルファイル、MCP メモリ、ベクターストア、Git リポジトリ）にわたるナレッジベースの管理、取り込み、同期、検索。ユーザーが知識システム全体で保存・整理・同期・重複排除・検索を行いたい場合に使用します。

Use when writing, checking or cleaning up SOPs and runbooks. Generates them with sop_generator.py, checks 5W2H completeness and links with runbook_validator.py and ingests an existing knowledge base with kb_ingester.py.

Knowledge base management, ingestion, synchronization, and retrieval across multiple storage layers (local files, MCP memory, vector stores, Git repositories). Used when users want to save, organize, sync, deduplicate, or search their knowledge system.

Knowledge base management, ingestion, sync, and retrieval across multiple storage layers (local files, MCP memory, vector stores, Git repos). Use when the user wants to save, organize, sync, deduplicate, or search across their knowledge systems.

Expert patterns for Kotlin Coroutines and Flow, covering structured concurrency, error handling, and testing.

Kotlin Coroutines and Flow patterns for Android and KMP — structured concurrency, Flow operators, StateFlow, error handling, and testing. Use when writing coroutines or Flow code on Android or KMP, or debugging cancellation and concurrency.

Android および KMP 向けの Kotlin コルーチンと Flow パターン — 構造化並行性、Flow オペレーター、StateFlow、エラーハンドリング、テスト。

Kotlin coroutines and Flow patterns in Android and KMP—structured concurrency, Flow operators, StateFlow, error handling, and testing.

JetBrains Exposed ORM パターン（DSL クエリ、DAO パターン、トランザクション、HikariCP 接続プーリング、Flyway マイグレーション、リポジトリパターンを含む）。

JetBrains Exposed ORM patterns, including DSL queries, DAO patterns, transactions, HikariCP connection pooling, Flyway migrations, and repository patterns.

JetBrains Exposed ORM patterns including DSL queries, DAO pattern, transactions, HikariCP connection pooling, Flyway migrations, and repository pattern. Use when working with the Exposed ORM — DSL or DAO queries, transactions, pooling, or migrations.

Ktor server patterns including routing DSL, plugins, authentication, Koin DI, kotlinx.serialization, WebSockets, and testApplication testing. Use when building a Ktor server — routing, plugins, auth, DI, serialization, or tests.

Ktor サーバーパターン（ルーティング DSL、プラグイン、認証、Koin DI、kotlinx.serialization、WebSocket、testApplication テストを含む）。

Ktor server patterns, including routing DSL, plugins, authentication, Koin DI, kotlinx.serialization, WebSockets, and testApplication testing.

Coroutine'ler, null safety ve DSL builder'lar ile sağlam, verimli ve sürdürülebilir Kotlin uygulamaları oluşturmak için idiomatic Kotlin kalıpları, en iyi uygulamalar ve konvansiyonlar.

Idiomatic Kotlin patterns, best practices, and conventions for building robust, efficient, and maintainable Kotlin applications with coroutines, null safety, and DSL builders. Use when writing or reviewing Kotlin code and idiomatic structure or null safety is in question.

Idiomatic Kotlin patterns, best practices, and conventions for building robust, efficient, and maintainable Kotlin applications, including coroutines, null safety, and DSL builders.

コルーチン、null 安全性、DSL ビルダーを使用して堅牢・効率的・保守性の高い Kotlin アプリケーションを構築するための慣用的な Kotlin パターン、ベストプラクティス、規約。

Idiomatic Kotlin patterns, best practices, and conventions for building robust, efficient, and maintainable Kotlin applications with coroutines, null safety, and DSL builders.

Patrones idiomáticos de Kotlin, buenas prácticas y convenciones para construir aplicaciones Kotlin robustas, eficientes y mantenibles con coroutines, null safety y builders de DSL.

Kotlin testing patterns with Kotest, MockK, coroutine testing, property-based testing, and Kover coverage. Follows TDD methodology with idiomatic Kotlin practices. Use when writing Kotlin tests with Kotest or MockK, or testing coroutines and checking coverage.

Kotlin testing patterns using Kotest, MockK, coroutine testing, property-based testing, and Kover coverage. Follows TDD methodology and idiomatic Kotlin practices.

Patrones de pruebas Kotlin con Kotest, MockK, pruebas de coroutines, pruebas basadas en propiedades y cobertura con Kover. Sigue la metodología TDD con prácticas idiomáticas de Kotlin.

Kotlin testing patterns with Kotest, MockK, coroutine testing, property-based testing, and Kover coverage. Follows TDD methodology with idiomatic Kotlin practices.

Kotest, MockK, coroutine testi, property-based testing ve Kover coverage ile Kotlin test kalıpları. İdiomatic Kotlin uygulamalarıyla TDD metodolojisini takip eder.

KQL language expertise for writing correct, efficient Kusto Query Language queries. Covers syntax gotchas, join patterns, dynamic types, datetime pitfalls, regex patterns, serialization, memory management, result-size discipline, and advanced functions (geo, vector, graph). USE THIS SKILL whenever writing, debugging, or reviewing KQL queries — even simple ones — because the gotchas section prevents the most common errors that waste tool calls and cause expensive retry cascades. Trigger on: KQL, Kusto, ADX, Azure Data Explorer, Fabric Real-Time Intelligence, EventHouse, Log Analytics, log analysis, data exploration, time series, anomaly detection, summarize, where clause, join, extend, project, let statement, parse operator, extract function, any mention of pipe-forward query syntax.

Expert Kubernetes architect specializing in cloud-native infrastructure, advanced GitOps workflows (ArgoCD/Flux), and enterprise container orchestration.

Use when building a Kubernetes operator or CRD (controller-runtime, kubebuilder, operator-sdk, KOPF), before writing the controller. Validates CRDs with crd_validator.py, lints reconcile loops with reconcile_lint.py and scores OperatorHub capability level.

Kubernetes workload patterns, resource management, RBAC, probes, autoscaling, ConfigMap/Secret handling, and kubectl debugging for production-grade deployments. Use when writing or reviewing Kubernetes manifests, or debugging probes, RBAC, autoscaling, or resource limits.

Electronic lab notebook API integration. Access notebooks, manage entries/attachments, backup notebooks, integrate with Protocols.io/Jupyter/REDCap, for programmatic ELN workflows.

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.

Use when asked for a premium single-file HTML landing page with 3D CSS, GSAP scroll effects and parallax. Locks positioning in a short intake, validates the palette with brand_palette_validator.py and the output with html_validator.py.

Use when asked for a landing, marketing or campaign page as a Next.js TSX component with Tailwind. Scaffolds it with landing_page_scaffolder.py using PAS, AIDA or BAB copy, SEO meta and Core Web Vitals targets.

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.

Investigate AI traces, observations, exceptions, latency, sessions, prompts, datasets, annotation queues, and scores through Langfuse MCP. Use when the request names Langfuse or asks to diagnose recorded AI behavior.

Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when: langgraph, langchain agent, stateful agent, agent graph, react agent.

Senior Laravel Engineer role for production-grade, maintainable, and idiomatic Laravel solutions. Focuses on clean architecture, security, performance, and modern standards (Laravel 10/11+).

Laravel architecture patterns, routing/controllers, Eloquent ORM, service layers, queues, events, caching, and API resources for production apps. Use when building or reviewing Laravel apps — controllers, Eloquent, service layers, queues, or API resources.

Laravel architecture patterns, routing/controllers, Eloquent ORM, service layers, queues, events, caching, and API resources for production apps.

Patrones de arquitectura Laravel, routing/controladores, Eloquent ORM, capas de servicio, colas, eventos, caché y API resources para aplicaciones en producción.

Discover and evaluate Laravel packages via LaraPlugins.io MCP. Use when the user wants to find plugins, check package health, or assess Laravel/PHP compatibility.

Discover and evaluate Laravel packages via LaraPlugins.io MCP. Use when the user wants to find plugins, check package health, or assess Laravel/PHP compatibility.

Laravel security best practices — authentication, authorization, Eloquent safety, CSRF, XSS prevention, API security, and secure deployment configurations. Use when reviewing Laravel auth, Eloquent safety, CSRF, XSS, API security, or deployment configuration.

Laravel security best practices for authn/authz, validation, CSRF, mass assignment, file uploads, secrets, rate limiting, and secure deployment.

Laravel セキュリティベストプラクティス：認証・認可、バリデーション、CSRF、一括割当、ファイルアップロード、シークレット管理、レート制限、安全なデプロイメント

Buenas prácticas de seguridad en Laravel para autenticación/autorización, validación, CSRF, asignación masiva, subida de archivos, secretos, limitación de velocidad y despliegue seguro.

Laravel での TDD：PHPUnit と Pest、ファクトリー、データベーステスト、フェイク、カバレッジターゲット

Test-driven development for Laravel with PHPUnit and Pest, factories, database testing, fakes, and coverage targets.

Laravel testing strategies with PHPUnit, Pest, model factories, HTTP tests, Sanctum authentication testing, mocking, and coverage. Use when writing Laravel tests with PHPUnit or Pest, or driving a Laravel feature test-first.

Desarrollo guiado por pruebas para Laravel con PHPUnit y Pest, factories, pruebas de base de datos, fakes y objetivos de cobertura.