fix(anthropic): send tool definitions in standardized format

sentry_sdk/consts.py

@@ -563,6 +563,12 @@ class SPANDATA:
     Example: [{"type": "text", "text": "You are a helpful assistant."},{"type": "text", "text": "Be concise and clear."}]
     """
 
+    GEN_AI_TOOL_DEFINITIONS = "gen_ai.tool.definitions"
+    """
+    The definitions of the tools available to the model.
+    Example: [{"name": "get_weather", "description": "Get the weather for a given location", "type": "function", "parameters": {"location": "string"}}]
+    """
+
     GEN_AI_REQUEST_MESSAGES = "gen_ai.request.messages"
     """
     The messages passed to the model. The "content" can be a string or an array of objects.

sentry_sdk/integrations/anthropic.py

@@ -13,6 +13,7 @@
     truncate_and_annotate_messages,
     get_start_span_function,
     transform_anthropic_content_part,
+    _normalize_data,
 )
 from sentry_sdk.consts import OP, SPANDATA, SPANSTATUS
 from sentry_sdk.integrations import _check_minimum_version, DidNotEnable, Integration
@@ -368,6 +369,29 @@ def _transform_system_instructions(
     ]
 
 
+def _transform_anthropic_tools(
+    tools: "Iterable[ToolUnionParam]",
+) -> "list[dict[str, Any]]":
+    transformed_tools = []
+    for tool in tools:
+        if not isinstance(tool, dict):
+            continue
+
+        transformed_tool = {
+            "name": tool.get("name"),
+            "description": tool.get("description"),
+            "type": "function",
+        }
+
+        input_schema = tool.get("input_schema")
+        if input_schema:
+            transformed_tool["parameters"] = _normalize_data(input_schema, unpack=False)
+
+        transformed_tools.append(transformed_tool)
+
+    return transformed_tools
+
+
 def _set_common_input_data(
     span: "Span",
     integration: "AnthropicIntegration",
@@ -463,6 +487,13 @@ def _set_common_input_data(
 
     if tools is not None and _is_given(tools) and len(tools) > 0:  # type: ignore
         span.set_data(SPANDATA.GEN_AI_REQUEST_AVAILABLE_TOOLS, safe_serialize(tools))
+        if should_send_default_pii() and integration.include_prompts:
+            set_data_normalized(
+                span,
+                SPANDATA.GEN_AI_TOOL_DEFINITIONS,
+                _transform_anthropic_tools(tools),
+                unpack=False,
+            )
 
 
 def _set_create_input_data(

tests/integrations/anthropic/test_anthropic_tools_definitions.py

@@ -0,0 +1,108 @@
+import pytest
+from unittest import mock
+import json
+
+from anthropic import Anthropic
+from anthropic.types.message import Message
+from anthropic.types.usage import Usage
+
+try:
+    from anthropic.types.text_block import TextBlock
+except ImportError:
+    from anthropic.types.content_block import ContentBlock as TextBlock
+
+from sentry_sdk import start_transaction
+from sentry_sdk.consts import OP, SPANDATA
+from sentry_sdk.integrations.anthropic import AnthropicIntegration
+
+
+EXAMPLE_MESSAGE = Message(
+    id="msg_01XFDUDYJgAACzvnptvVoYEL",
+    model="model",
+    role="assistant",
+    content=[TextBlock(type="text", text="Hi, I'm Claude.")],
+    type="message",
+    stop_reason="end_turn",
+    usage=Usage(input_tokens=10, output_tokens=20),
+)
+
+TOOLS = [
+    {
+        "name": "get_weather",
+        "description": "Get the current weather in a given location",
+        "input_schema": {
+            "type": "object",
+            "properties": {
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
+                },
+                "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
+            },
+            "required": ["location"],
+        },
+    }
+]
+
+
+@pytest.mark.parametrize(
+    "send_default_pii, include_prompts",
+    [
+        (True, True),
+        (True, False),
+        (False, True),
+        (False, False),
+    ],
+)
+def test_tool_definitions_in_create_message(
+    sentry_init, capture_events, send_default_pii, include_prompts
+):
+    sentry_init(
+        integrations=[AnthropicIntegration(include_prompts=include_prompts)],
+        traces_sample_rate=1.0,
+        send_default_pii=send_default_pii,
+    )
+    events = capture_events()
+    client = Anthropic(api_key="z")
+    client.messages._post = mock.Mock(return_value=EXAMPLE_MESSAGE)
+
+    messages = [
+        {
+            "role": "user",
+            "content": "What is the weather in San Francisco?",
+        }
+    ]
+
+    with start_transaction(name="anthropic"):
+        client.messages.create(
+            max_tokens=1024,
+            messages=messages,
+            model="model",
+            tools=TOOLS,
+        )
+
+    assert len(events) == 1
+    (event,) = events
+    (span,) = event["spans"]
+
+    assert span["op"] == OP.GEN_AI_CHAT
+
+    # Check old available_tools attribute (always present if tools provided)
+    assert SPANDATA.GEN_AI_REQUEST_AVAILABLE_TOOLS in span["data"]
+    available_tools = json.loads(span["data"][SPANDATA.GEN_AI_REQUEST_AVAILABLE_TOOLS])
+    assert available_tools == TOOLS
+
+    # Check new tool.definitions attribute (only present if PII and prompts enabled)
+    if send_default_pii and include_prompts:
+        assert SPANDATA.GEN_AI_TOOL_DEFINITIONS in span["data"]
+        tool_definitions = json.loads(span["data"][SPANDATA.GEN_AI_TOOL_DEFINITIONS])
+        assert len(tool_definitions) == 1
+        assert tool_definitions[0]["name"] == "get_weather"
+        assert (
+            tool_definitions[0]["description"]
+            == "Get the current weather in a given location"
+        )
+        assert tool_definitions[0]["type"] == "function"
+        assert tool_definitions[0]["parameters"] == TOOLS[0]["input_schema"]
+    else:
+        assert SPANDATA.GEN_AI_TOOL_DEFINITIONS not in span["data"]