OpenInference Claude Agent SDK Instrumentation

Python auto-instrumentation for the Claude Agent SDK (Python). Traces query() and ClaudeSDKClient as OpenInference AGENT spans with prompt input, result output, session/model metadata, token counts, and tool child spans via hook injection.

• query() – One span per call (one-off sessions).
• ClaudeSDKClient – One span per response turn: each time you iterate receive_response() (or receive_messages()), a span is created for that turn. Use for continuous conversations.
• Tools – Tool calls are captured as child TOOL spans via Claude Agent SDK hooks (PreToolUse/PostToolUse/PostToolUseFailure).

For detailed LLM and tool spans inside agent runs, use openinference-instrumentation-anthropic together with this package; the Agent SDK uses the Anthropic API under the hood.

Traces are OpenTelemetry-compatible and can be sent to any OTLP collector, Arize Phoenix (local), Phoenix Cloud, or Arize AX.

Installation

pip install openinference-instrumentation-claude-agent-sdk

Quickstart

pip install openinference-instrumentation-claude-agent-sdk claude-agent-sdk arize-phoenix opentelemetry-sdk opentelemetry-exporter-otlp

Option A – Phoenix Cloud: Create a free Phoenix Cloud account, create a space, and set PHOENIX_COLLECTOR_ENDPOINT and PHOENIX_API_KEY. Use your collector endpoint (e.g. https://<host>/v1/traces) as endpoint below.

Option B – Local Phoenix: Start Phoenix, then run your script:

python -m phoenix.server.main serve

Then in Python:

import asyncio
import os
from claude_agent_sdk import query, ClaudeAgentOptions
from openinference.instrumentation.claude_agent_sdk import ClaudeAgentSDKInstrumentor
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk import trace as trace_sdk
from opentelemetry.sdk.trace.export import SimpleSpanProcessor

# Phoenix Cloud: set PHOENIX_COLLECTOR_ENDPOINT (and PHOENIX_API_KEY for auth). Else local.
endpoint = os.environ.get("PHOENIX_COLLECTOR_ENDPOINT", "http://127.0.0.1:6006/v1/traces")
tracer_provider = trace_sdk.TracerProvider()
tracer_provider.add_span_processor(SimpleSpanProcessor(OTLPSpanExporter(endpoint)))
ClaudeAgentSDKInstrumentor().instrument(tracer_provider=tracer_provider)

async def main():
    async for message in query(
        prompt="What files are in this directory?",
        options=ClaudeAgentOptions(allowed_tools=["Bash", "Glob"]),
    ):
        if hasattr(message, "result"):
            print(message.result)

asyncio.run(main())

View traces in Phoenix Cloud, at http://localhost:6006 when running Phoenix locally, or in Arize AX.

Examples

Run the examples in this repo:

pip install -r examples/requirements.txt
export ANTHROPIC_API_KEY=your-key
python examples/basic_query.py

See examples/README.md for details.

What is instrumented

• query() – Each call is wrapped in a single AGENT span named ClaudeAgentSDK.query with:

  • Input: prompt text or JSON (for async message iterables)
  • Output: result text/JSON from the SDK result message
  • Metadata: session.id, llm.model_name, token counts, and llm.cost.total when available
  • Tools: TOOL child spans created via SDK hooks

• ClaudeSDKClient – For multi-turn conversations:

  • connect(prompt=...) and query(prompt) record the prompt for the next response.
  • Each receive_response() iteration is wrapped in an AGENT span named ClaudeAgentSDK.ClaudeSDKClient.receive_response with the same input/output/metadata/tool spans as above.

Child LLM/tool spans (from the SDK’s internal Anthropic usage) are not created by this package; add openinference-instrumentation-anthropic and instrument Anthropic for that.

More Info

• More info on OpenInference and Phoenix
• More info on OpenInference and Arize AX