Blockchain

This skill performs differential topologically associating domain (TAD) analysis using HiCExplorer's hicDifferentialTAD tool. It compares Hi-C contact matrices between two conditions based on existing TAD definitions to identify significantly altered chromatin domains.

機能要件と非機能要件の分類と定義スキル。要件を適切なカテゴリに分類し、漏れなく体系的に管理するための方法論を提供する。Anchors:• ISO/IEC 25010 品質モデル / 適用: NFR分類と品質特性定義 / 目的: 8品質特性による網羅的カバレッジ• Don't Make Me Think (Steve Krug) / 適用: ユーザビリティ要件定義 / 目的: 直感性と認知負荷の測定基準• Software Requirements (Karl Wiegers) / 適用: 要件品質検証 / 目的: SMART原則による検証可能性確保Trigger:Use when classifying requirements into functional and non-functional categories, defining measurable quality attributes for NFRs, or validating requirements completeness and consistency.requirements, functional, non-functional, NFR, quality attributes, ISO 25010, SMART criteria, measurability

This skill enables Claude to generate Kubernetes deployment manifests, services, and related configurations following best practices. It should be used when the user asks to create a new Kubernetes deployment, service, ingress, or other related resources. Claude will generate YAML files for Deployments, Services, ConfigMaps, Secrets, Ingress, and Horizontal Pod Autoscalers. Use this skill when the user mentions "Kubernetes deployment", "K8s deployment", "create service", "define ingress", or asks for a manifest for any K8s resource.

Detects leaked API keys, tokens, passwords, and credentials in code with pre-commit hooks, CI checks, scanning rules, and remediation procedures. Use for "secret scanning", "credential detection", "API key leaks", or "secret management".

構造化ログのスキーマ設計、ログレベル設計、PIIマスキング、JSONログ実装を支援するスキル。ログ要件整理から検証までを一貫して整理する。Anchors:• Observability Engineering / 適用: ログ設計 / 目的: 可観測性向上• 12-Factor App / 適用: 構造化ログ / 目的: JSONログ標準化Trigger:Use when designing JSON log schemas, defining log levels, applying PII masking, or improving observability.structured logging, json logs, log schema, log levels, pii masking

Use when optimizing MCP server usage to reduce token overhead. Helps select appropriate servers based on task type.

データ変換パイプラインの設計・実装・検証を整理するスキル。スキーママッピング、ETL設計、品質確認までの実務フローを提供する。Anchors:• Designing Data-Intensive Applications / 適用: データモデリング / 目的: 変換の整合性確保• Designing Data-Intensive Applications / 適用: スキーマ設計 / 目的: マッピングの明確化• Designing Data-Intensive Applications / 適用: パイプライン設計 / 目的: 伸縮性と監視性の確保Trigger:Use when designing data transformation pipelines, defining schema mappings, implementing ETL processes, or optimizing data flows.data transformation, schema mapping, etl design, pipeline optimization, data modeling

Assembles relevant context for agent spawns with prioritized ranking. Ranks packages by relevance, enforces token budgets with graduated zones, captures error patterns for learning, and supports configurable per-agent retrieval limits.

API認証ドキュメント（OAuth 2.0/PKCE、API Key、JWT、トークン管理）の作成と図解を支援するスキル。認証フローの説明、トークン取得手順、セキュリティ注意点をわかりやすく整理します。Anchors:• OAuth 2.0 Simplified / 適用: フロー図解 / 目的: 正確な説明と用語整理• Web Application Security / 適用: セキュリティ注意点 / 目的: 安全な認証ドキュメント• API Documentation Best Practices / 適用: ドキュメント構成 / 目的: 読みやすさの担保Trigger:Use when writing authentication docs, creating OAuth flow diagrams, documenting token management, or preparing quickstart guides for API auth.

This skill allows Claude to conduct comprehensive security audits of code, infrastructure, and configurations. It leverages various tools within the security-pro-pack plugin, including vulnerability scanning, compliance checking, cryptography review, and infrastructure security analysis. Use this skill when a user requests a "security audit," "vulnerability assessment," "compliance review," or any task involving identifying and mitigating security risks. It helps to ensure code and systems adhere to security best practices and compliance standards. Activates when you request "performing security audits" functionality.

Use when building GitHub-based features - Explains auth token usage, Gist reading/writing and rendering helpers.

This skill optimizes prompts for Large Language Models (LLMs) to reduce token usage, lower costs, and improve performance. It analyzes the prompt, identifies areas for simplification and redundancy removal, and rewrites the prompt to be more concise and effective. It is used when the user wants to reduce LLM costs, improve response speed, or enhance the quality of LLM outputs by optimizing the prompt. Trigger terms include "optimize prompt", "reduce LLM cost", "improve prompt performance", "rewrite prompt", "prompt optimization".

This skill enables Claude to create Application Performance Monitoring (APM) dashboards. It is triggered when the user requests the creation of a new APM dashboard, monitoring dashboard, or a dashboard for application performance. The skill helps define key metrics and visualizations for monitoring application health, performance, and user experience across multiple platforms like Grafana and Datadog. Use this skill when the user needs assistance setting up a new monitoring solution or expanding an existing one. The plugin supports the creation of dashboards focusing on golden signals, request metrics, resource utilization, database metrics, cache metrics, business metrics, and error tracking.

This skill enables Claude to create intelligent alerting rules for proactive performance monitoring. It is triggered when the user requests to "create alerts", "define monitoring rules", or "set up alerting". The skill helps define thresholds, routing, and escalation policies, and offers options for multi-category alert creation, including latency, error rate, throughput, resource utilization, availability, and SLO violation alerts. It is useful for Site Reliability Engineers (SREs) and DevOps teams looking to improve system observability.

現代的なSREプラクティスに基づくObservabilityと監視システム設計の専門知識。メトリクス、ログ、トレースの3本柱とダッシュボード設計、SLI/SLO定義を提供。Anchors:• Google SRE Book / 適用: Observabilityアーキテクチャ・SLI/SLO設計 / 目的: 本番環境対応の監視システム• Observability Engineering (Honeycomb) / 適用: モダンObservabilityパターン / 目的: 高カーディナリティObservability実装• The Art of Monitoring (James Turnbull) / 適用: 実践的な監視実装 / 目的: エンドツーエンドの監視ワークフローTrigger:Use when designing observability systems, implementing metrics collection, setting up distributed tracing, creating dashboards, defining SLIs/SLOs, or establishing logging strategies.observability, monitoring, metrics, traces, logs, SLI, SLO, Prometheus, Grafana, OpenTelemetry

This skill enables Claude to detect infrastructure drift from a desired state. It uses the `drift-detect` command to identify discrepancies between the current infrastructure configuration and the intended configuration, as defined in infrastructure-as-code tools like Terraform. Use this skill when the user asks to check for infrastructure drift, identify configuration changes, or ensure that the current infrastructure matches the desired state. It is particularly useful in DevOps workflows for maintaining infrastructure consistency and preventing configuration errors. Trigger this skill when the user mentions "drift detection," "infrastructure changes," "configuration drift," or requests a "drift report."

Package claudefiles components into a valid Claude Code plugin

一貫性と拡張性を両立するデザインシステムの基盤設計を支援するスキル。デザイントークン、コンポーネント規約、Figma/コード同期を体系化する。Anchors:• Atomic Design / 適用: コンポーネント階層設計 / 目的: 構造の一貫性確保• Design Tokens / 適用: トークン管理 / 目的: 再利用性の向上• Clean Architecture / 適用: 依存関係設計 / 目的: 責務分離Trigger:Use when designing a design system, defining design tokens, or establishing component and Figma-code synchronization rules.design system architecture, design tokens, figma sync, component guidelines

Comprehensive guide for creating React components in the squared package and squareone app. Use this skill when creating new components, setting up component structure, implementing CSS Modules styling, writing Storybook stories, or setting up component tests. Covers TypeScript patterns (type vs interface, no React.FC), CSS Modules with design tokens, compound component patterns, Storybook integration, and vitest testing.

This skill allows Claude to construct and configure neural network architectures using the neural-network-builder plugin. It should be used when the user requests the creation of a new neural network, modification of an existing one, or assistance with defining the layers, parameters, and training process. The skill is triggered by requests involving terms like "build a neural network," "define network architecture," "configure layers," or specific mentions of neural network types (e.g., "CNN," "RNN," "transformer").