generating-database-seed-data

Process this skill enables AI assistant to generate realistic test data and database seed scripts for development and testing environments. it uses faker libraries to create realistic data, maintains relational integrity, and allows configurable data volumes. u... Use when working with databases or data models. Trigger with phrases like 'database', 'query', or 'schema'.

跳到安装

仓库: jeremylongshore/claude-code-plugins-plus-skills
最近来源活动: 2026年7月17日 22:18
检测到的 SKILL.md 语言: 英语
星标: 2,604
分支: 378

安装方式

默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。

用 Codex 或 Claude 帮你安装复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。

直接命令不会经过审查 Prompt；运行前请先检查来源。

npx skills add https://github.com/jeremylongshore/claude-code-plugins-plus-skills --skill generating-database-seed-data

命令会保持在同一行。复制前请横向滚动并检查完整内容。

想先保存到本地？可下载 SkillsMP 当前能够提供的文件。

检查来源文件

决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。

文件资源管理器

4 个文件

SKILL.md

来源说明 · 只读预览

返回搜索返回安装

clerk-core-workflow-a

Implement user sign-up and sign-in flows with Clerk. Use when building authentication UI, customizing sign-in experience, or implementing OAuth social login. Trigger with phrases like "clerk sign-in", "clerk sign-up", "clerk login flow", "clerk OAuth", "clerk social login".

2026-07-23

clerk-core-workflow-b

Implement session management and middleware with Clerk. Use when managing user sessions, configuring route protection, or implementing token refresh and custom JWT templates. Trigger with phrases like "clerk session", "clerk middleware", "clerk route protection", "clerk token", "clerk JWT".

2026-07-23

clerk-enterprise-rbac

Configure enterprise SSO, role-based access control, and organization management. Use when implementing SSO integration, configuring role-based permissions, or setting up organization-level controls. Trigger with phrases like "clerk SSO", "clerk RBAC", "clerk enterprise", "clerk roles", "clerk permissions", "clerk organizations".

2026-07-23

查看这个仓库的全部 Skills

Data Seeder Generator

Overview

Generate realistic database seed scripts that populate development and testing environments with representative data. This skill creates seed data that respects foreign key relationships, unique constraints, check constraints, and data type validations using Faker libraries (faker.js, Faker for Python, or raw SQL with random functions).

Prerequisites

Database schema definition (SQL DDL, ORM models, or Prisma schema) to understand table structures

Target database connection for schema introspection (optional, can work from DDL files)

Faker library available: @faker-js/faker (Node.js), faker (Python), or Bogus (.NET)

Knowledge of referential integrity constraints (foreign keys, cascades)

Target data volume per table (e.g., 100 users, 1000 orders, 5000 line items)

Instructions

Analyze the database schema to catalog all tables, columns, data types, constraints, and foreign key relationships. Build a dependency graph where parent tables (referenced by foreign keys) must be seeded before child tables.

Determine the seeding order by topologically sorting the dependency graph. Tables with no foreign keys are seeded first (users, categories, products), then tables referencing them (orders, reviews), then junction tables and deeply nested tables last.

Map each column to an appropriate Faker generator based on column name and data type:

first_name, last_name -> faker.person.firstName(), faker.person.lastName()
email -> faker.internet.email() with unique enforcement
phone -> faker.phone.number()
address, city, state, zip -> faker.location.*
created_at, updated_at -> faker.date.between({ from: '2023-01-01', to: '2024-12-31' })
price, amount -> faker.commerce.price({ min: 1, max: 999 })
description, bio -> faker.lorem.paragraph()
status -> Random selection from CHECK constraint values or enum values

Data Seeder Generator

Overview

Prerequisites

Database schema definition (SQL DDL, ORM models, or Prisma schema) to understand table structures

Target database connection for schema introspection (optional, can work from DDL files)

Faker library available: @faker-js/faker (Node.js), faker (Python), or Bogus (.NET)

Knowledge of referential integrity constraints (foreign keys, cascades)

Target data volume per table (e.g., 100 users, 1000 orders, 5000 line items)

Instructions

Map each column to an appropriate Faker generator based on column name and data type:

first_name, last_name -> faker.person.firstName(), faker.person.lastName()
email -> faker.internet.email() with unique enforcement
phone -> faker.phone.number()
address, city, state, zip -> faker.location.*
created_at, updated_at -> faker.date.between({ from: '2023-01-01', to: '2024-12-31' })
price, amount -> faker.commerce.price({ min: 1, max: 999 })
description, bio -> faker.lorem.paragraph()
status -> Random selection from CHECK constraint values or enum values

name	generating-database-seed-data
description	Process this skill enables AI assistant to generate realistic test data and database seed scripts for development and testing environments. it uses faker libraries to create realistic data, maintains relational integrity, and allows configurable data volumes. u... Use when working with databases or data models. Trigger with phrases like 'database', 'query', or 'schema'.
allowed-tools	Read, Write, Edit, Grep, Glob, Bash(cmd:*)
version	1.22.0
author	Jeremy Longshore <jeremy@intentsolutions.io>
license	MIT
tags	["database","testing","database-seed"]
compatibility	Designed for Claude Code, also compatible with Codex and OpenClaw

name	generating-database-seed-data
description	Process this skill enables AI assistant to generate realistic test data and database seed scripts for development and testing environments. it uses faker libraries to create realistic data, maintains relational integrity, and allows configurable data volumes. u... Use when working with databases or data models. Trigger with phrases like 'database', 'query', or 'schema'.
allowed-tools	Read, Write, Edit, Grep, Glob, Bash(cmd:*)
version	1.22.0
author	Jeremy Longshore <jeremy@intentsolutions.io>
license	MIT
tags	["database","testing","database-seed"]
compatibility	Designed for Claude Code, also compatible with Codex and OpenClaw

Error	Cause	Solution
Foreign key constraint violation during seeding	Child records reference parent IDs that do not exist	Verify seeding order follows dependency graph; ensure parent seed completes before child seed starts
Unique constraint violation	Faker generated duplicate values for unique columns	Track generated values in a Set; use `faker.helpers.unique()` wrapper; append sequential suffix for high-volume unique fields
CHECK constraint violation	Generated value outside allowed range or not in enum list	Read CHECK constraints from schema; configure Faker min/max ranges; restrict enum selection to valid values
Seed script too slow for large volumes	Individual INSERT statements instead of batch operations	Use batch inserts (`INSERT INTO ... VALUES (...), (...), (...)`); use COPY command for PostgreSQL; disable indexes during bulk insert
Unrealistic data distribution	All records have uniform random values	Use weighted random selection for status fields; apply Zipf distribution for popularity-based relationships; generate time-series data with realistic patterns

generating-database-seed-data

安装方式

检查来源文件

Data Seeder Generator

Overview

Prerequisites

Instructions

Data Seeder Generator

Overview

Prerequisites

Instructions

Output

Error Handling

Examples

Resources

generating-database-seed-data

来源信息

安装方式

检查来源文件

同仓库更多 Skills

同仓库更多 Skills

Data Seeder Generator

Overview

Prerequisites

Instructions

Data Seeder Generator

Overview

Prerequisites

Instructions

Output

Error Handling

Examples

Resources