資料庫

Evaluates agent performance, rule compliance, and workflow quality. Provides systematic evaluation using code-based, model-based, and human grading methods.

This skill provides project-specific coding conventions, architectural principles, repository structure standards, testing patterns, and contribution guidelines for the better-chatbot project (https://github.com/cgoinglove/better-chatbot). Use this skill when contributing to or working with better-chatbot to understand the design philosophy and ensure code follows established patterns. Includes: API architecture deep-dive, three-tier tool system (MCP/Workflow/Default), component design patterns, database repository patterns, architectural principles (progressive enhancement, defensive programming, streaming-first), practical templates for adding features (tools, routes, repositories). Use when: working in better-chatbot repository, contributing features/fixes, understanding architectural decisions, following server action validators, implementing tools/workflows, setting up Playwright tests, adding API routes, designing database queries, building UI components, handling multi-AI provider integration Keywords: better-chatbot, chatbot contribution, better-chatbot standards, chatbot development, AI chatbot patterns, API architecture, three-tier tool system, repository pattern, progressive enhancement, defensive programming, streaming-first, compound component pattern, Next.js chatbot, Vercel AI SDK chatbot, MCP tools, workflow builder, server action validators, tool abstraction, DAG workflows, shared business logic, safe() wrapper, tool lifecycle

DuckDB data lakehouse development with Dagster orchestration and Apache Iceberg integration for floe-platform. Use when: (1) Building data pipelines with DuckDB as compute engine, (2) Configuring dbt-duckdb with Polaris plugin, (3) Reading/writing Iceberg tables via Polaris catalog, (4) Creating Dagster assets with DuckDB, (5) Designing catalog-first lakehouse architecture, (6) Connecting to REST catalogs with inline credentials.

マルチテナント（顧客別DB分離）のDB運用・マイグレーション・調査に使う。

Эксперт DB replication. Используй для настройки репликации MySQL, PostgreSQL, MongoDB, failover и high availability.

Analyze ProtonDB game compatibility and provide optimized Linux gaming configurations. Use when checking if games work on Linux, optimizing launch options, or troubleshooting gaming issues on AMD GPU + Wayland + Arch Linux.

Manages Prisma schema operations, database migrations, and data relationships for the digital marketplace. Use when working with database schema changes, product data models, or subscription management tables.

Run multiple agent tasks in parallel cloud sandboxes with real-time progress monitoring, achieving 2x throughput vs sequential execution. Use for multi-repo tasks, independent bug fixes, concurrent feature development, or team workflows requiring parallel workstreams. Supports session management, result aggregation, and local teleport. Triggers on "parallel tasks", "multiple repos", "concurrent work", "parallel sessions", "multi-repo".

Docker Compose configuration template and validation logic for MetaSaver monorepos. Includes 4 required standards (PostgreSQL service with project-prefixed env vars like RUGBYCRM_POSTGRES_USER or METASAVER_SILVER_POSTGRES_USER for multi-db, project-specific naming for containers and networks, volumes section, service health checks). Use when creating or auditing docker-compose.yml files.

Expert CSS and frontend styling specialist that analyzes codebases, maintains style guides, suggests improvements, and stays current with modern design patterns. Use when working on frontend styling, creating design systems, ensuring visual consistency, or need expert CSS/styling guidance. Integrates with oracle, summoner, and wizard.

Creates git commits for already-staged changes following conventional commit format. ALWAYS check git diff --cached FIRST to verify staged changes. Use when user asks to commit staged changes, create a commit, or mentions commit-staged. Generates concise one-liner messages or overview with bullet points. Never stages files - only commits what user already staged.

SQLAlchemy Python SQL toolkit and ORM with powerful query builder, relationship mapping, and database migrations via Alembic

Create and harden systemd service unit files following modern best practices. Use when writing new systemd units for web applications, background workers, or daemons, or when hardening existing services with security sandboxing and isolation features. Covers service types, dependencies, restart policies, security options, and filesystem restrictions.

Define database models and schemas with proper data types, constraints, relationships, and validation rules. Use this skill when creating or modifying database models, ORM entities, schema definitions, or data validation layers. When working on Prisma schema files, TypeORM entities, Drizzle schema definitions, Mongoose models, database model classes, files defining table structures and relationships, validation schemas for database entities, or files implementing data integrity constraints and cascading behaviors.

Build enterprise Blazor applications with MudBlazor component library. Use when creating forms, data grids, dialogs, navigation, theming, layout systems, or integrating with Neatoo domain objects. Covers installation, components, validation, data display, and enterprise patterns.

Drizzle ORMを使用したデータベース操作を支援。スキーマ変更、マイグレーション、シードデータ投入、DBリセットで使用。トリガー例：「DBを更新」「スキーマ変更」「テーブル追加」「カラム追加」「シード実行」「マイグレーション」

This skill should be used when the user asks to "access LSEG data", "query Refinitiv", "get market data from Refinitiv", "download fundamentals from LSEG", "access ESG scores", "convert RIC to ISIN", or needs the LSEG Data Library Python API.

Deploy and manage Docker containers on Cloudflare's global network alongside Workers. Use when building applications that need to run Python code, process large files (multi-GB zips, video transcoding), execute CLI tools, run AI inference, create code sandboxes, or any workload requiring more memory/CPU than Workers provide. Triggers include requests to run containers, execute arbitrary code, process large files, deploy backend services in Python/Go/Rust, or integrate heavyweight compute with Workers.

Async SQLAlchemy 2.0+ database patterns for FastAPI including session management, connection pooling, Alembic migrations, relationship loading strategies, and query optimization. Use when implementing database models, configuring async sessions, setting up migrations, optimizing queries, managing relationships, or when user mentions SQLAlchemy, async database, ORM, Alembic, database performance, or connection pooling.

SQL for data analysis with exploratory analysis, advanced aggregations, statistical functions, outlier detection, and business insights. 50+ real-world analytics queries.