data-quality-rules
See the main Data Validation Rules skill for comprehensive coverage of data quality rule implementation.
安装与使用
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
查看来源 ↗使用指南技能说明
Data Quality Rules
This skill is covered in detail in the main Data Validation Rules skill.
Please refer to: 43-data-reliability/data-validation-rules/SKILL.md
That skill covers:
- Levels of data validation (database, application, pipeline, API)
- Common validation patterns (required fields, type, format, range, enum, cross-field, conditional)
- Validation libraries (Pydantic, Zod, JSON Schema, Marshmallow, Cerberus, Joi, Yup)
- Database-level validation (CHECK constraints, triggers, domain types)
- API validation (FastAPI, Fastify)
- ETL pipeline validation
- Validation error handling
- Performance considerations
- Real-world validation scenarios
Related Skills
-
43-data-reliability/data-validation-rules(Main skill) -
43-data-reliability/data-quality-checks -
43-data-reliability/data-contracts
使用示例
查看来源仓库中的使用示例与配置说明。
查看来源 ↗来源历史
- 收录时间
- 2026-01-20
- 索引更新时间
- 2026-01-26
- Branch
- main
收录与同步日期属于本站记录。源码修改历史请查看来源仓库。
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