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概要と使いどころ
Owns data as an asset — governance, quality, the warehouse and semantic layer, analytics capability, and the governance of models built on top. Use this for a decision about how data is collected, stored, defined, or shared; when numbers disagree between teams; when deciding what to build in-house versus buy; when standing up a data function; or when an AI or model decision needs governance rather than engineering.
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Builds and operates data pipelines — ingestion, transformation, orchestration, quality testing, and reliability of data delivery. Use this to design or debug a pipeline, decide batch versus streaming, add data quality checks, handle late or duplicate data, or work out why a dashboard's numbers changed without anyone changing the dashboard.
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。
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical 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。
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
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。
World-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence. Includes experiment design, feature engineering, model evaluation, and stakeholder communication. Use when designing experiments, building predictive models, performing causal analysis, or driving data-driven decisions.
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。
**IMPORTANT**: Any change to React or Next.js code must read through this skill first. React and Next.js guidelines from Vercel Engineering covering visual instability, layout shifts, CLS, flickering, hydration issues, and font loading.
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。
Comprehensive security engineering skill for application security, penetration testing, security architecture, and compliance auditing. Includes security assessment tools, threat modeling, crypto implementation, and security automation. Use when designing security architecture, conducting penetration tests, implementing cryptography, or performing security audits.
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Context window monitoring and budget management. Keeps orchestrator at 15-30% context usage while subagents get full 200k tokens. Provides warnings at thresholds, context-aware summarization triggers, and wave-level budget planning.
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。
Dynamic context injection, mode switching (dev/review/research), selective loading, and strategic compaction for token optimization.
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。
Iterative Five Whys root cause analysis drilling from symptoms to fundamentals
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。
Execute tasks through systematic exploration, pruning, and expansion using Tree of Thoughts methodology with meta-judge evaluation specifications and multi-agent evaluation
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。
Use when errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source of invalid data or incorrect behavior
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。
Display the current state of the FPF knowledge base
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Guide for setup arXiv paper search MCP server using Docker MCP
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Guide for setup Codemap CLI for intelligent codebase visualization and navigation
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This skill should be used when need prioritize what changed code in repository human must review.
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 missing test coverage for your local code changes by generating new test files (covers uncommitted and untracked changes, or the latest commit if everything is committed). Use when you want write tests for new logic or increase test coverage.
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Update and maintain project documentation for local code changes using multi-agent workflow with tech-writer agents. Covers docs/, READMEs, JSDoc, and API documentation.
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Use when executing implementation plans with independent tasks in the current session or facing 3+ independent issues that can be investigated without shared state or dependencies - dispatches fresh subagent for each task with code review between tasks, enabling fast iteration with quality gates
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Use after writing tests to assess coverage quality across structural, mutation, requirements, and API/integration dimensions; organized knowledge for choosing and interpreting coverage analyses.
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。
Use when tackling complex reasoning tasks requiring step-by-step logic, multi-step arithmetic, commonsense reasoning, symbolic manipulation, or problems where simple prompting fails - provides comprehensive guide to Chain-of-Thought and related prompting techniques (Zero-shot CoT, Self-Consistency, Tree of Thoughts, Least-to-Most, ReAct, PAL, Reflexion) with templates, decision matrices, and research-backed patterns
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。
Guide for setup Context7 MCP server to load documentation for specific technologies.
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。
Use when creating or editing skills, before deployment, to verify they work under pressure and resist rationalization - applies RED-GREEN-REFACTOR cycle to process documentation by running baseline without skill, writing to address failures, iterating to close loopholes
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。
Guide for setup Serena MCP server for semantic code retrieval and editing capabilities
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。