Schema Evolution Manager

Manages schema evolution and compatibility across data systems

509 stars

Best use case

Schema Evolution Manager is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Manages schema evolution and compatibility across data systems

Teams using Schema Evolution Manager should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/schema-evolution-manager/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/data-engineering-analytics/skills/schema-evolution-manager/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/schema-evolution-manager/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How Schema Evolution Manager Compares

Feature / Agent	Schema Evolution Manager	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

Manages schema evolution and compatibility across data systems

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Schema Evolution Manager

## Overview

Manages schema evolution and compatibility across data systems. This skill ensures safe schema changes that maintain backward and forward compatibility.

## Capabilities

- Schema compatibility checking (Avro, Protobuf, JSON Schema)
- Breaking change detection
- Migration script generation
- Version management
- Schema registry operations
- Backward/forward compatibility validation
- Schema documentation generation
- Cross-system schema synchronization

## Input Schema

```json
{
  "currentSchema": "object",
  "proposedSchema": "object",
  "schemaFormat": "avro|protobuf|jsonschema|ddl",
  "compatibilityMode": "backward|forward|full|none"
}
```

## Output Schema

```json
{
  "compatible": "boolean",
  "breakingChanges": ["object"],
  "migrationScript": "string",
  "recommendations": ["string"],
  "versionInfo": "object"
}
```

## Target Processes

- Streaming Pipeline
- ETL/ELT Pipeline
- Data Catalog
- Pipeline Migration

## Usage Guidelines

1. Provide current and proposed schema definitions
2. Specify schema format for proper parsing
3. Define compatibility mode based on system requirements
4. Review breaking changes before proceeding with migration

## Best Practices

- Always test schema changes in non-production first
- Use schema registry for centralized schema management
- Document schema versions and changes
- Plan migration strategies for breaking changes
- Coordinate schema changes across dependent systems