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moai-domain-database摩艾域数据库

Agent Skill

用于辅助数据库表结构、查询语句、迁移脚本和数据维护任务。它适合让 Agent 分析 schema、编写 SQL、排查查询问题、整理索引或生成迁移建议。使用时需要明确数据库类型、连接环境和目标表,区分只读分析与写入变更;涉及删除、更新、迁移和批量导入时,应优先 dry-run、备份或事务保护,避免误操作。

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周安装

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GitHub Stars

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CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:moai-domain-database(摩艾域数据库)
来源仓库:https://github.com/modu-ai/moai-adk
仓库路径:skills/moai-domain-database
安装命令:
npx skills add https://github.com/modu-ai/moai-adk --skill moai-domain-database
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/modu-ai/moai-adk --skill moai-domain-database

简介

moai-domain-database 用于辅助数据库表结构、查询语句和迁移脚本的编写与维护。

  • 适用于分析 schema、编写 SQL、排查查询问题或生成迁移建议的场景。
  • 使用时需明确数据库类型、连接环境和目标表,区分只读分析与写入变更。
  • 涉及删除、更新或批量导入时,应优先 dry-run 或备份以避免误操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Database Domain Specialist

Quick Reference

Enterprise Database Expertise - Comprehensive database patterns and implementations covering PostgreSQL, MongoDB, Redis, Oracle, and advanced data management for scalable modern applications.

Core Capabilities:

  • PostgreSQL: Advanced relational patterns, optimization, and scaling
  • MongoDB: Document modeling, aggregation, and NoSQL performance tuning
  • Redis: In-memory caching, real-time analytics, and distributed systems
  • Oracle: Enterprise patterns, PL/SQL, partitioning, and hierarchical queries
  • Multi-Database: Hybrid architectures and data integration patterns
  • Performance: Query optimization, indexing strategies, and scaling
  • Operations: Connection management, migrations, and monitoring

When to Use:

  • Designing database schemas and data models
  • Implementing caching strategies and performance optimization
  • Building scalable data architectures
  • Working with multi-database systems
  • Optimizing database queries and performance

Implementation Guide

Quick Start Workflow

Database Stack Initialization:

Create a DatabaseManager instance and configure multiple database connections. Set up PostgreSQL with connection string, pool size of 20, and query logging enabled. Configure MongoDB with connection string, database name, and sharding enabled. Configure Redis with connection string, max connections of 50, and clustering enabled. Use the unified interface to query user data with profile and analytics across all database types.

Single Database Operations:

Run PostgreSQL schema migrations using the migration command with the database type and migration file path. Execute MongoDB aggregation pipelines by specifying the collection name and pipeline JSON file. Warm Redis cache by specifying key patterns and TTL values.

Core Components

PostgreSQL Module:

  • Advanced schema design and constraints
  • Complex query optimization and indexing
  • Window functions and CTEs
  • Partitioning and materialized views
  • Connection pooling and performance tuning

MongoDB Module:

  • Document modeling and schema design
  • Aggregation pipelines for analytics
  • Indexing strategies and performance
  • Sharding and scaling patterns
  • Data consistency and validation

Redis Module:

  • Multi-layer caching strategies
  • Real-time analytics and counting
  • Distributed locking and coordination
  • Pub/sub messaging and streams
  • Advanced data structures including HyperLogLog and Geo

Oracle Module:

  • Hierarchical and recursive query patterns (CONNECT BY)
  • PL/SQL procedures, packages, and batch operations
  • Partitioning strategies (range, list, hash, composite)
  • Enterprise features and statement caching
  • LOB handling and large data processing

Advanced Patterns

Multi-Database Architecture

Polyglot Persistence Pattern:

Create a DataRouter class that initializes connections to PostgreSQL, MongoDB, Redis, and Oracle. Implement get_user_profile method that retrieves structured user data from PostgreSQL or Oracle, flexible profile data from MongoDB, and real-time status from Redis, then merges all data sources. Implement update_user_data method that routes structured data updates to PostgreSQL/Oracle, profile data updates to MongoDB, and real-time data updates to Redis, followed by cache invalidation.

Data Synchronization:

Create a DataSyncManager class that synchronizes user data across databases. Implement sync_user_data method that retrieves user from PostgreSQL, creates a search document for MongoDB, upserts to the MongoDB search collection, creates cache data, and updates Redis cache with TTL.

Performance Optimization

Query Performance Analysis:

For PostgreSQL, execute EXPLAIN ANALYZE BUFFERS on queries and use a QueryAnalyzer to generate optimization suggestions. For MongoDB, create an AggregationOptimizer to analyze and optimize aggregation pipelines. For Redis, retrieve info metrics and use a PerformanceAnalyzer to generate recommendations.

Scaling Strategies:

Configure PostgreSQL read replicas by providing replica connection URLs. Set up MongoDB sharding with shard key and number of shards. Configure Redis clustering by providing node URLs for the cluster.


Works Well With

Complementary Skills:

  • moai-domain-backend - API integration and business logic
  • moai-foundation-core - Database migration and schema management
  • moai-workflow-project - Database project setup and configuration
  • moai-platform-supabase - Supabase database integration patterns
  • moai-platform-neon - Neon database integration patterns
  • moai-platform-firestore - Firestore database integration patterns

Technology Integration:

  • ORMs and ODMs including SQLAlchemy, Mongoose, and TypeORM
  • Connection pooling with PgBouncer and connection pools
  • Migration tools including Alembic, Flyway, and Data Pump
  • Monitoring with pg_stat_statements, MongoDB Atlas, and Oracle AWR
  • python-oracledb for Oracle connectivity and PL/SQL execution
  • Cache invalidation and synchronization

Technology Stack

Relational Database:

  • PostgreSQL 14+ as primary database
  • MySQL 8.0+ as alternative
  • Connection pooling with PgBouncer and SQLAlchemy

NoSQL Database:

  • MongoDB 6.0+ as primary document store
  • Document modeling and validation
  • Aggregation framework
  • Sharding and replication

In-Memory Database:

  • Redis 7.0+ as primary cache
  • Redis Stack for advanced features
  • Clustering and high availability
  • Advanced data structures

Enterprise Database:

  • Oracle 19c+ / 21c+ for enterprise workloads
  • python-oracledb (successor to cx_Oracle)
  • PL/SQL procedures and packages
  • Partitioning and advanced analytics

Supporting Tools:

  • Migration tools including Alembic and Flyway
  • Monitoring with Prometheus and Grafana
  • ORMs and ODMs including SQLAlchemy and Mongoose
  • Connection management utilities

Performance Features:

  • Query optimization and analysis
  • Index management and strategies
  • Caching layers and invalidation
  • Load balancing and failover

Resources

For working code examples, see examples.md.

For detailed implementation patterns and database-specific optimizations, see the modules directory.

Status: Production Ready Last Updated: 2026-01-11 Maintained by: MoAI-ADK Database Team

Common Rationalizations

RationalizationReality
"I do not need an index, the table is small"Tables grow. The missing index that is invisible at 1K rows becomes a production incident at 1M rows.
"I will add the migration later"Schema changes without migrations are unreproducible. Every change must have a reversible migration script.
"This query works fine in development"Development databases have tiny datasets. Production query plans differ dramatically at scale. Explain analyze first.
"NoSQL does not need schema design"Schemaless does not mean designless. Document structure decisions affect every query and index.
"I will just add a column, it is non-breaking"Adding a NOT NULL column without a default breaks existing inserts. Column additions need default values or migration backfills.
"Connection pooling is handled by the framework"Framework defaults are generic. Pool size, timeout, and idle limits must be tuned to the workload.

Red Flags

  • Schema change committed without a corresponding migration file
  • Query uses SELECT * in production code instead of explicit column list
  • No index exists for columns used in WHERE, JOIN, or ORDER BY clauses
  • Connection string hardcoded in source instead of environment variable
  • Transaction scope spans user-facing HTTP request duration (long-held locks)
  • No EXPLAIN ANALYZE output for new queries touching large tables

Verification

  • Migration file exists for every schema change (show migration file list)
  • Indexes exist for frequently queried columns (show index definitions)
  • EXPLAIN ANALYZE run for new queries on representative data (show output)
  • Connection credentials sourced from environment variables
  • Transaction scopes are minimal and do not span I/O waits
  • Backup and restore procedure documented and tested
  • Connection pool settings configured with explicit size and timeout

Cloud Vendor Guide (absorbed from moai-platform-database-cloud)

Cloud database platform selection and configuration for Neon, Supabase, and Firebase Firestore.

Quick Decision Guide

NeedPlatform
Serverless PostgreSQL with auto-scalingNeon
Database branching for CI/CD previewsNeon branching
Edge-compatible connection poolingNeon + Neon Proxy
Vector search (pgvector) for AI/MLSupabase
Row-Level Security for multi-tenant appsSupabase RLS
Real-time subscriptions + full-stackSupabase
Mobile-first with offline syncFirebase Firestore
Cross-platform (iOS/Android/Web)Firebase Firestore

Neon (Serverless PostgreSQL)

Key features: Auto-scaling compute, scale-to-zero, database branching, pg_bouncer pooling.

Setup:

npm install @neondatabase/serverless
# Connection string: postgresql://user:pass@ep-xxx.neon.tech/dbname?sslmode=require

Branch workflow: Create a branch per PR (neonctl branches create --name pr-123), run migrations, test, delete on merge. Zero cost during idle periods.

Supabase (PostgreSQL 16)

Key features: pgvector, Row-Level Security, real-time subscriptions, built-in auth/storage.

RLS policy pattern:

CREATE POLICY "users_own_data" ON items
  FOR ALL USING (auth.uid() = user_id);

pgvector search: SELECT * FROM embeddings ORDER BY embedding <-> $1 LIMIT 10;

Firebase Firestore (NoSQL)

Key features: Real-time sync, offline caching, Security Rules, mobile SDKs.

Security Rules pattern:

match /users/{userId} {
  allow read, write: if request.auth.uid == userId;
}

Offline persistence: Enable via enableIndexedDbPersistence(db) (web) or SDK default (mobile).

Full platform reference: modules/cloud-database.md

Refactor Notes

R4 audit verdict (2026-04-23): REFACTOR — MERGE target (absorbs moai-platform-database-cloud) with additional restructuring needed SPEC: SPEC-V3R2-WF-001 §6.2 line 263 Refactor scope (deferred to future sub-SPEC):

  • Separate moai-domain-db-docs workflow skill from this query/schema design skill
  • Extract cloud vendor deep-dives (Neon, Supabase, Firestore) into dedicated Level-3 modules
  • Consolidate overlapping ORM pattern content across database types

This skill is retained in v3.0 but its body will be restructured in a follow-up SPEC. Cloud vendor content absorbed from moai-platform-database-cloud in Wave 1.2.

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

26.21%
按下载量换算185

OpenCode

25.71%
按下载量换算182

Antigravity

19.36%
按下载量换算137

Codex

12.52%
按下载量换算88

Cursor

6.97%
按下载量换算49

Gemini CLI

3.61%
按下载量换算25

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安装前确认

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