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Write CLAUDE MD files that define API versioning strategy by specifying current active versions, deprecated versions with sunset dates, versioning method (URL-based or header-based), and clear version schemas. These files communicate to AI assistants which API versions to use, which ones to avoid, and how breaking changes are managed—preventing AI from generating code using deprecated endpoints.

Why API Versioning Matters for AI-Assisted Development

When an AI assistant interacts with your codebase, it needs to understand not just the current API structure, but how that API evolves over time. Without clear versioning documentation, AI tools may inadvertently use deprecated endpoints or misunderstand breaking changes. A well-crafted CLAUDE MD file bridges this gap by providing explicit guidance on your versioning philosophy and current API state.

Modern APIs face several challenges that make versioning essential. First, you need to maintain backward compatibility while introducing new features. Second, different clients may require different API versions. Third, AI assistants need consistent rules to generate correct code. A CLAUDE MD file addresses all these concerns by establishing clear conventions that the AI can follow.

Structuring Your CLAUDE MD for API Versioning

Your CLAUDE MD file should contain several key sections that cover different aspects of API versioning. Start with an overview that explains your versioning approach, whether you use URL-based versioning, header-based versioning, or another strategy.

# API Versioning Strategy

## Current Version
- Active: v2
- Deprecated: v1 (sunset date: 2026-06-01)

## Versioning Method
URL-based: /api/v1/, /api/v2/

This structure immediately tells an AI assistant which version to use and which ones to avoid. Include clear indicators of deprecated versions with sunset dates to prevent the AI from generating code that uses outdated endpoints.

Defining Version Schemas

Each API version should have its schema clearly documented in your CLAUDE MD file. Specify the request and response structures for major endpoints, highlighting any differences between versions.

// v2 User Endpoint Response Schema
{
  "id": "string (UUID)",
  "email": "string",
  "profile": {
    "name": "string",
    "avatar_url": "string (optional in v1, required in v2)"
  },
  "created_at": "ISO 8601 datetime",
  "updated_at": "ISO 8601 datetime"
}

By including schema examples, you help the AI understand exactly what data structures to expect and generate. This reduces errors and improves the quality of code the AI produces.

Handling Breaking Changes

Document your policy for breaking changes clearly. Specify what constitutes a breaking change in your API and how you communicate these changes to clients. Include information about deprecation notices, migration guides, and timeline expectations.

For example, you might specify that breaking changes only happen in major versions, that deprecation warnings are issued three months in advance, and that each breaking change includes a migration script. When the AI understands these rules, it can generate code that follows best practices and helps users migrate properly.

Version Selection Rules

Include explicit rules about when to use which API version. Specify default versions for new integrations versus migration paths for existing clients. The AI should know whether to recommend v2 for all new code or if v1 is still acceptable in certain contexts.

## Version Selection Guidelines

- New projects: Always use v2
- Existing v1 integrations: Plan migration to v2 within 6 months
- Internal tools: Migrated to v2 as of 2026-01-01
- Partner APIs: v2 required for new partnerships

These clear guidelines prevent the AI from generating inconsistent code that mixes versions inappropriately.

Error Handling Across Versions

Different API versions may handle errors differently. Document the error response formats for each version so the AI can generate appropriate error-handling code. Include information about status codes, error message formats, and any version-specific error handling requirements.

// v2 Error Response Format
{
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Invalid email format",
    "details": [
      {"field": "email", "issue": "must be valid email"}
    ]
  }
}

Testing Version-Specific Code

Include guidance on how to test code that interacts with different API versions. Specify which test environments use which versions, how to mock different API responses, and what test coverage expectations exist for version-specific functionality.

Best Practices Summary

Creating effective CLAUDE MD files for API versioning requires clarity and completeness. Keep these principles in mind when writing your documentation. First, be explicit about which version is current and default. Second, document breaking changes and deprecation timelines. Third, include practical code examples for common scenarios. Fourth, specify error handling differences between versions. Fifth, provide clear migration guidance for moving between versions.

Complete CLAUDE.md Example for Versioning

# API Versioning Guide for AI Assistants

## Current Status (Last updated: 2026-03-20)
- **Active version:** v3
- **Recommended for new projects:** v3
- **In maintenance mode:** v2 (sunset: 2026-09-01)
- **Deprecated:** v1 (sunset: 2026-03-01)

## Version Selection Rules
- New integrations: Use v3 exclusively
- Existing v2 clients: Plan migration by 2026-06-01
- Legacy v1 clients: Critical—migrate by 2026-03-01 or service will disconnect

## v3 Key Differences from v2
- Request body now requires `api_version: "v3"` header
- All timestamps use RFC 3339 format (was Unix milliseconds in v2)
- Pagination changed from offset/limit to cursor-based (performance improvement)
- Error responses include `request_id` field for debugging

## Breaking Changes History
| Version | Change | Migration | Timeline |
|---------|--------|-----------|----------|
| v2 → v3 | Pagination method | Provide cursor library | 2026-03-01 to 2026-06-01 |
| v1 → v2 | Auth headers | API key migration script | 2025-12-01 to 2026-03-01 |

## Request Examples

### v3 (Current)
```json
{
  "api_version": "v3",
  "method": "GET /api/v3/users/123",
  "headers": {
    "Authorization": "Bearer TOKEN",
    "X-Request-ID": "uuid-here"
  }
}

v2 (Deprecated)

{
  "method": "GET /api/v2/users/123",
  "headers": {
    "Authorization": "Bearer TOKEN"
  }
}

Error Response Schemas by Version

v3 Error Response

{
  "error": {
    "code": "INVALID_VERSION",
    "message": "API version v1 is deprecated",
    "request_id": "req_abc123",
    "deprecated_by": "v2",
    "migration_docs": "https://docs.example.com/v2-migration"
  }
}

v2 Error Response

{
  "error_code": "401",
  "error_message": "Unauthorized"
}

Migration Script

For v2 → v3, provide AI with this Python example:

import requests
from datetime import datetime

def upgrade_request_v2_to_v3(v2_request):
    headers = v2_request['headers']
    headers['api_version'] = 'v3'
    headers['X-Request-ID'] = uuid.uuid4()

    # Convert timestamps from ms to RFC 3339
    if 'timestamps' in v2_request['body']:
        for field, ts_ms in v2_request['body']['timestamps'].items():
            dt = datetime.fromtimestamp(ts_ms/1000)
            v2_request['body'][field] = dt.isoformat() + 'Z'

    return v2_request

```

When your CLAUDE MD file is clear and well-organized, AI assistants can generate more accurate, version-appropriate code. This leads to fewer integration errors, smoother migrations, and better developer experience overall.

Impact Metrics

Without proper CLAUDE.md versioning:

With detailed CLAUDE.md versioning:

Team productivity impact:

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