anth-migration-deep-dive
Migrate to Claude API from OpenAI, Gemini, or other LLM providers. Use when switching from GPT-4 to Claude, migrating from Text Completions, or building a multi-provider abstraction layer. Trigger with phrases like "migrate to claude", "openai to anthropic", "switch from gpt to claude", "multi-provider llm".
Best use case
anth-migration-deep-dive is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Migrate to Claude API from OpenAI, Gemini, or other LLM providers. Use when switching from GPT-4 to Claude, migrating from Text Completions, or building a multi-provider abstraction layer. Trigger with phrases like "migrate to claude", "openai to anthropic", "switch from gpt to claude", "multi-provider llm".
Teams using anth-migration-deep-dive 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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/anth-migration-deep-dive/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How anth-migration-deep-dive Compares
| Feature / Agent | anth-migration-deep-dive | 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?
Migrate to Claude API from OpenAI, Gemini, or other LLM providers. Use when switching from GPT-4 to Claude, migrating from Text Completions, or building a multi-provider abstraction layer. Trigger with phrases like "migrate to claude", "openai to anthropic", "switch from gpt to claude", "multi-provider llm".
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.
Related Guides
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ChatGPT vs Claude for Agent Skills
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SKILL.md Source
# Anthropic Migration Deep Dive
## Overview
Migration strategies for switching to Claude from OpenAI, Google, or other LLM providers, including API mapping, prompt translation, and multi-provider abstraction.
## OpenAI to Anthropic API Mapping
| OpenAI | Anthropic | Notes |
|--------|-----------|-------|
| `openai.ChatCompletion.create()` | `anthropic.messages.create()` | Different response shape |
| `model: "gpt-4"` | `model: "claude-sonnet-4-20250514"` | Different model IDs |
| `messages: [{role, content}]` | `messages: [{role, content}]` | Same format |
| `functions` / `tools` | `tools` | Similar but different schema key names |
| `function_call` | `tool_choice` | Different naming |
| `response.choices[0].message.content` | `response.content[0].text` | Different access path |
| `stream: true` → yields chunks | `stream: true` → SSE events | Different event format |
| System message in `messages[]` | `system` parameter (separate) | Claude separates system prompt |
| `n` (multiple completions) | Not supported | Use multiple requests |
| `logprobs` | Not supported | N/A |
## Side-by-Side Code Comparison
```python
# === OpenAI ===
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="gpt-4",
messages=[
{"role": "system", "content": "You are helpful."},
{"role": "user", "content": "Hello"}
],
max_tokens=1024,
temperature=0.7
)
text = response.choices[0].message.content
# === Anthropic ===
import anthropic
client = anthropic.Anthropic()
response = client.messages.create(
model="claude-sonnet-4-20250514",
system="You are helpful.", # System prompt is separate
messages=[
{"role": "user", "content": "Hello"}
],
max_tokens=1024, # Required (not optional)
temperature=0.7
)
text = response.content[0].text
```
## Tool Use Migration
```python
# OpenAI tools format
openai_tools = [{
"type": "function",
"function": {
"name": "get_weather",
"parameters": {"type": "object", "properties": {"city": {"type": "string"}}}
}
}]
# Anthropic tools format — flatter structure
anthropic_tools = [{
"name": "get_weather",
"description": "Get weather for a city", # Required in Anthropic
"input_schema": {"type": "object", "properties": {"city": {"type": "string"}}}
}]
```
## Multi-Provider Abstraction
```python
from abc import ABC, abstractmethod
class LLMProvider(ABC):
@abstractmethod
def complete(self, prompt: str, system: str = "", **kwargs) -> str: ...
class AnthropicProvider(LLMProvider):
def __init__(self):
import anthropic
self.client = anthropic.Anthropic()
def complete(self, prompt: str, system: str = "", **kwargs) -> str:
msg = self.client.messages.create(
model=kwargs.get("model", "claude-sonnet-4-20250514"),
max_tokens=kwargs.get("max_tokens", 1024),
system=system,
messages=[{"role": "user", "content": prompt}]
)
return msg.content[0].text
class OpenAIProvider(LLMProvider):
def __init__(self):
from openai import OpenAI
self.client = OpenAI()
def complete(self, prompt: str, system: str = "", **kwargs) -> str:
messages = []
if system:
messages.append({"role": "system", "content": system})
messages.append({"role": "user", "content": prompt})
resp = self.client.chat.completions.create(
model=kwargs.get("model", "gpt-4"),
messages=messages,
max_tokens=kwargs.get("max_tokens", 1024)
)
return resp.choices[0].message.content
```
## Migration Checklist
- [ ] Map model names (GPT-4 → Claude Sonnet, GPT-3.5 → Claude Haiku)
- [ ] Move system prompts from `messages[]` to `system` parameter
- [ ] Update response access path (`.choices[0].message.content` → `.content[0].text`)
- [ ] Make `max_tokens` explicit (required in Anthropic, optional in OpenAI)
- [ ] Update tool definitions to Anthropic format
- [ ] Test prompt behavior (Claude may respond differently to same prompts)
- [ ] Update error handling for Anthropic error types
## Resources
- [Anthropic vs OpenAI Migration](https://docs.anthropic.com/en/docs/about-claude/models)
- [Messages API Reference](https://docs.anthropic.com/en/api/messages)
## Next Steps
For advanced debugging, see `anth-advanced-troubleshooting`.Related Skills
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