diff --git a/CHANGELOG.md b/CHANGELOG.md
index 46905c5..51ba465 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -7,6 +7,13 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## [2.0.2] - 2026-02-05
+
+### Fixed
+
+- **tool_choice format incompatibility** - Removed `extra_body` tool_choice hack for Claude backend; PydanticAI handles tool_choice natively for Anthropic, preventing infinite tool call loops
+- **CI trigger** - Changed workflow trigger from `release:published` to `push:tags:v[0-9]*`
+
 ## [2.0.1] - 2026-02-05
 
 ### Fixed
diff --git a/pyproject.toml b/pyproject.toml
index ba6488d..71ad7d4 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "tatlock"
-version = "2.0.1"
+version = "2.0.2"
 description = "OpenAI-compatible API with Ollama backend"
 requires-python = ">=3.12"
 dependencies = []
diff --git a/src/agents/tatlock.py b/src/agents/tatlock.py
index 0d6d3db..b65b9a9 100644
--- a/src/agents/tatlock.py
+++ b/src/agents/tatlock.py
@@ -494,13 +494,13 @@ class TatlockAgent(AgentInterface):
                 )
 
         # Run with scoped tools and tracker
-        # Force tool_choice: required to make LLM actually call tools
-        from pydantic_ai.settings import ModelSettings
+        # Force tool_choice to make LLM actually call tools
+        from src.anthropic.model_selector import get_tool_choice_settings
         result = await scoped_agent.run(
             enriched_message,
             message_history=pydantic_history if pydantic_history else None,
             deps=tool_tracker,
-            model_settings=ModelSettings(extra_body={"tool_choice": "required"})
+            model_settings=get_tool_choice_settings(),
         )
 
         logger.info(
@@ -624,7 +624,6 @@ class TatlockAgent(AgentInterface):
                 - tool_outputs: Dict mapping tool names to their outputs
                 - raw_output: The agent's raw text output
         """
-        from pydantic_ai.settings import ModelSettings
         from pydantic_ai.messages import (
             ModelRequest,
             ModelResponse,
@@ -684,11 +683,12 @@ class TatlockAgent(AgentInterface):
                 )
 
         # Run with scoped tools and tracker
+        from src.anthropic.model_selector import get_tool_choice_settings
         result = await scoped_agent.run(
             enriched_message,
             message_history=pydantic_history if pydantic_history else None,
             deps=tool_tracker,
-            model_settings=ModelSettings(extra_body={"tool_choice": "required"})
+            model_settings=get_tool_choice_settings(),
         )
 
         # Extract tool calls and results from the agent's messages
diff --git a/src/anthropic/__init__.py b/src/anthropic/__init__.py
index e101c66..7c46682 100644
--- a/src/anthropic/__init__.py
+++ b/src/anthropic/__init__.py
@@ -7,11 +7,13 @@ Provides model selection with automatic fallback between Claude and Ollama.
 from src.anthropic.model_selector import (
     check_claude_health,
     get_model,
+    get_tool_choice_settings,
     is_claude_available,
 )
 
 __all__ = [
     "check_claude_health",
     "get_model",
+    "get_tool_choice_settings",
     "is_claude_available",
 ]
diff --git a/src/anthropic/model_selector.py b/src/anthropic/model_selector.py
index 1465547..04c7461 100644
--- a/src/anthropic/model_selector.py
+++ b/src/anthropic/model_selector.py
@@ -132,6 +132,23 @@ def get_model(prefer_cloud: bool | None = None) -> Union[AnthropicModel, OpenAIC
     )
 
 
+def get_tool_choice_settings() -> 'ModelSettings':
+    """
+    Get model_settings for forcing tool calls on the first request.
+
+    For Claude: PydanticAI handles tool_choice natively, so no extra_body needed.
+    For Ollama: Pass tool_choice="required" via extra_body to force tool calling.
+    """
+    from pydantic_ai.settings import ModelSettings
+
+    if is_claude_available() and config.PREFER_CLOUD_BACKEND:
+        # PydanticAI's Anthropic model handles tool_choice internally
+        return ModelSettings()
+    else:
+        # Ollama needs explicit tool_choice via extra_body
+        return ModelSettings(extra_body={"tool_choice": "required"})
+
+
 def get_model_info() -> dict:
     """
     Get information about the current model configuration.