データ・AIのスキル

Master SQL query optimization, indexing strategies, and EXPLAIN analysis to dramatically improve database performance and eliminate slow queries. Use when debugging slow queries, designing database schemas, or optimizing application performance.

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 comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.

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。

Select and optimize embedding models for semantic search and RAG applications. Use when choosing embedding models, implementing chunking strategies, or optimizing embedding quality for specific domains.

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 GDPR-compliant data handling with consent management, data subject rights, and privacy by design. Use when building systems that process EU personal data, implementing privacy controls, or conducting GDPR compliance reviews.

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。

Preflight and diagnose the ten known failure modes for ML training on NVIDIA DGX Spark. Use when a training run on DGX Spark fails to start, OOMs below the 128GB limit, slows down mid-run, or before any multi-hour training job on GB10.

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。

Master Unity ECS (Entity Component System) with DOTS, Jobs, and Burst for high-performance game development. Use when building data-oriented games, optimizing performance, or working with large entity counts.

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。

Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall.

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。

This skill should be used when the user asks to "optimize a prompt", "improve prompt performance", "design a prompt template", "write better prompts", "debug prompt issues", "use chain-of-thought", "structured prompting", "few-shot prompting", or wants to apply advanced prompt engineering patterns for production LLM applications.

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 the user needs a local file converted between common image, audio, video, document, or data formats. Select installed tools, preserve originals, and verify the output.

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。

Optimize Apache Spark jobs with partitioning, caching, shuffle optimization, and memory tuning. Use when improving Spark performance, debugging slow jobs, or scaling data processing pipelines.

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 this skill when designing or reviewing a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features

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 data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.

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 this skill when building or modifying Minecraft server plugins for Paper, Spigot, or Bukkit, including plugin.yml setup, commands, listeners, schedulers, player state, team or arena systems, persistent progression, economy or profile data, configuration files, Adventure text, and version-safe API usage. Trigger for requests like "build a Minecraft plugin", "add a Paper command", "fix a Bukkit listener", "create plugin.yml", "implement a minigame mechanic", "add a perk or quest system", or "debug server plugin 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。

A persistent, compounding knowledge base combining Karpathy's LLM Wiki pattern with a structured knowledge graph. Ingest documents once — the LLM writes wiki pages, extracts entities/relations into the graph, and stores raw content for evidence retrieval. Knowledge accumulates and cross-references; it is never re-derived from scratch.

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。

PostgreSQL-specific code review assistant focusing on PostgreSQL best practices, anti-patterns, and unique quality standards. Covers JSONB operations, array usage, custom types, schema design, function optimization, and PostgreSQL-exclusive security features like Row Level Security (RLS).

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。

Migrates Oracle PL/SQL stored procedures to PostgreSQL PL/pgSQL. Translates Oracle-specific syntax, preserves method signatures and type-anchored parameters, leverages orafce where appropriate, and applies explicit collation mapping (`COLLATE "C"` only when appropriate, locale collations when required). Use when converting Oracle stored procedures or functions to PostgreSQL equivalents during a database migration.

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。

Build and run evaluators for AI/LLM applications using Phoenix.

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。

Systematic Power BI performance troubleshooting prompt for identifying, diagnosing, and resolving performance issues in Power BI models, reports, and queries.

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。

Plain-English translation layer for non-technical Copilot CLI users. Translates every approval prompt, error message, and technical output into clear, jargon-free English with color-coded risk indicators.

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。

Build production RAG pipelines and persistent agent memory using Pinecone as the vector database backend. ALWAYS USE THIS SKILL when the user mentions Pinecone, wants to index documents for semantic search, build a retrieval-augmented generation system, store agent memory across sessions, implement hybrid search, or connect an LLM to a searchable knowledge base — even if they don't say "Pinecone" explicitly. Also use when the user asks about vector databases for RAG, namespace isolation for multi-tenant agents, embedding pipelines, or scaling a knowledge base beyond what local storage can handle. DO NOT use for local-only vector stores (Chroma, FAISS, pgvector) or pure keyword search with no semantic component.

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。

Migrates .NET/C# data access code from Oracle to PostgreSQL (Npgsql). Replaces Oracle NuGet packages, rewrites OracleConnection/OracleCommand/OracleDataReader usage, fixes DbType mappings, updates stored procedure invocation patterns, and adapts connection string configuration. Use when migrating the application code layer of a .NET project during an Oracle-to-PostgreSQL database migration.

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 Power BI DAX formula optimization prompt for improving performance, readability, and maintainability of DAX calculations.

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。

Generate or edit images via OpenRouter with the Gemini 3 Pro Image model. Use for prompt-only image generation, image edits, and multi-image compositing; supports 1K/2K/4K output.

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。

PostgreSQL-specific development assistant focusing on unique PostgreSQL features, advanced data types, and PostgreSQL-exclusive capabilities. Covers JSONB operations, array types, custom types, range/geometric types, full-text search, window functions, and PostgreSQL extensions ecosystem.

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。