Personal Finance

コンテキストウィンドウの制約内で情報を最適整理するためのスキル。トークン計測、優先順位付け、圧縮、検証の一連フローを提供する。Anchors:• High Performance Browser Networking / 適用: 計測とレイテンシ意識 / 目的: 予算内最適化• Designing Data-Intensive Applications / 適用: リソース制約下の設計 / 目的: 効率的な構造化• Progressive Disclosure パターン / 適用: 段階的情報開示 / 目的: 過剰読み込みの回避Trigger:Use when optimizing context window usage, measuring token budgets, prioritizing context elements, or applying compression techniques.context window optimization, token budget, context prioritization, compression, summarization

This skill enables Claude to define and track Service Level Agreements (SLAs), Service Level Indicators (SLIs), and Service Level Objectives (SLOs) for improved service reliability. It is triggered when the user needs to establish, monitor, or analyze service performance metrics. Use this skill when the user mentions "SLA", "SLI", "SLO", "error budget", "service reliability", or "track service performance". The skill helps to define key metrics, set targets, and monitor performance against those targets.

Industry-specific guide for implementing Fullstory in banking and financial services applications. Covers regulatory requirements (PCI DSS, GLBA, SOX), privacy controls for sensitive financial data, authentication flows, transaction monitoring, and fraud detection patterns. Includes detailed examples for retail banking, investment platforms, and payment applications.

This skill enables Claude to validate application performance against defined budgets. It's useful for identifying performance regressions early in the development lifecycle. The skill is triggered when the user mentions "performance budget", "validate budget", "performance regression", or requests a check against performance metrics like "page load times", "bundle sizes", "API response times", or "Lighthouse scores". The plugin validates against predefined thresholds and alerts on violations. It is especially helpful in CI/CD pipelines to prevent performance degradation in production.

This skill enables Claude to automatically detect performance regressions in a CI/CD pipeline. It analyzes performance metrics, such as response time and throughput, and compares them against baselines or thresholds. Use this skill when the user requests to "detect performance regressions", "analyze performance metrics for regressions", or "find performance degradation" in a CI/CD environment. The skill is also triggered when the user mentions "baseline comparison", "statistical significance analysis", or "performance budget violations". It helps identify and report performance issues early in the development cycle.

Generate SLA/SLO/SLI monitoring configurations for reliability tracking and error budget management. Activates for SLO setup, reliability targets, and error budget configuration.

This skill enables Claude to validate application performance against defined budgets. It's useful for identifying performance regressions early in the development lifecycle. The skill is triggered when the user mentions "performance budget", "validate budget", "performance regression", or requests a check against performance metrics like "page load times", "bundle sizes", "API response times", or "Lighthouse scores". The plugin validates against predefined thresholds and alerts on violations. It is especially helpful in CI/CD pipelines to prevent performance degradation in production.

This skill enables Claude to define and track Service Level Agreements (SLAs), Service Level Indicators (SLIs), and Service Level Objectives (SLOs) for improved service reliability. It is triggered when the user needs to establish, monitor, or analyze service performance metrics. Use this skill when the user mentions "SLA", "SLI", "SLO", "error budget", "service reliability", or "track service performance". The skill helps to define key metrics, set targets, and monitor performance against those targets.

This skill enables Claude to define and track Service Level Agreements (SLAs), Service Level Indicators (SLIs), and Service Level Objectives (SLOs) for improved service reliability. It is triggered when the user needs to establish, monitor, or analyze service performance metrics. Use this skill when the user mentions "SLA", "SLI", "SLO", "error budget", "service reliability", or "track service performance". The skill helps to define key metrics, set targets, and monitor performance against those targets.

This skill enables Claude to automatically detect performance regressions in a CI/CD pipeline. It analyzes performance metrics, such as response time and throughput, and compares them against baselines or thresholds. Use this skill when the user requests to "detect performance regressions", "analyze performance metrics for regressions", or "find performance degradation" in a CI/CD environment. The skill is also triggered when the user mentions "baseline comparison", "statistical significance analysis", or "performance budget violations". It helps identify and report performance issues early in the development cycle.

Performance testing guidance including load testing with k6, locust, and artillery, benchmarking strategies, profiling techniques, metrics analysis, performance budgets, and bottleneck identification. Use when setting up performance tests, analyzing system behavior under load, or optimizing application performance. Trigger keywords: performance testing, load testing, k6, locust, artillery, benchmarking, profiling, latency, throughput, performance budget, bottleneck, stress testing, scalability testing.

This skill enables Claude to automatically detect performance regressions in a CI/CD pipeline. It analyzes performance metrics, such as response time and throughput, and compares them against baselines or thresholds. Use this skill when the user requests to "detect performance regressions", "analyze performance metrics for regressions", or "find performance degradation" in a CI/CD environment. The skill is also triggered when the user mentions "baseline comparison", "statistical significance analysis", or "performance budget violations". It helps identify and report performance issues early in the development cycle.

This skill enables Claude to validate application performance against defined budgets. It's useful for identifying performance regressions early in the development lifecycle. The skill is triggered when the user mentions "performance budget", "validate budget", "performance regression", or requests a check against performance metrics like "page load times", "bundle sizes", "API response times", or "Lighthouse scores". The plugin validates against predefined thresholds and alerts on violations. It is especially helpful in CI/CD pipelines to prevent performance degradation in production.

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.

Use when delegating tasks to Gemini MCP. Two main use cases: (1) large-scale codebase investigation with @ syntax, (2) web search for latest information. Also for long log analysis, context optimization. Always request concrete report format without omissions or personal opinions.

R3F performance optimization—LOD (Level of Detail), frustum culling, instancing strategies, draw call reduction, frame budgets, lazy loading, and profiling tools. Use when optimizing render performance, handling large scenes, or debugging frame rate issues.

Compose technology-specific agent identity and patterns. Invoke before spawning agents (Developer, SSE, QA, Tech Lead, RE, Investigator) to enhance expertise based on project stack. Returns composed specialization block with token budgeting.

Designs multi-step agent workflows with tool usage, retry logic, state management, and budget controls. Provides orchestration diagrams, tool execution order, fallback strategies, and cost limits. Use for "AI agents", "agentic workflows", "multi-step AI", or "autonomous systems".

GitHub Actions の実行コストを最適化するためのスキル。コスト計測、削減施策の設計、実装、継続的な監視を一連で扱う。Anchors:• High Performance Browser Networking / 適用: 計測から改善する姿勢 / 目的: 速度とコストの可視化• Designing Data-Intensive Applications / 適用: 制約下の設計判断 / 目的: ランナー/ストレージの効率化• Continuous Delivery / 適用: 改善の反復 / 目的: 継続的最適化のサイクル化Trigger:Use when optimizing GitHub Actions workflow execution time, reducing runner costs, managing billing, or optimizing artifact storage and cache usage.github actions cost optimization, runner costs, workflow budget, artifact storage, caching strategy

Defines measurable performance budgets for bundle size, API latency, database queries, and render times. Provides enforcement strategies and monitoring plans. Use for "performance budgets", "performance monitoring", "web vitals", or "optimization targets".