feat(claude-agent-sdk): add instrumentation for @anthropic-ai/claude-agent-sdk#7603
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feat(claude-agent-sdk): add instrumentation for @anthropic-ai/claude-agent-sdk#7603mr-lee wants to merge 1 commit intoDataDog:masterfrom
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wconti27
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this would be really great, but much less useful without individual llm call spans bc that is where cost estimates come from |
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It seems like this is in your wheelhouse @sabrenner |
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@tlhunter yep, will be taking a look at this PR throughout the next week (we're aligning on some things internally) |
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@mr-lee could you please rebase and fix reported lint issues already? :) |
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…agent-sdk
Adds automatic instrumentation for the Claude Agent SDK, providing
full visibility into agentic sessions via APM tracing and LLM Obs.
Span hierarchy aligned with trajectory-spec APPENDIX-DD-LLMOBS-MAPPING:
agent (session)
└── agent (turn)
├── tool ({tool_name})
└── agent (subagent-{agent_type})
Key design decisions:
- Uses SDK's first-class hooks API (SessionStart, SessionEnd, Stop,
PreToolUse, PostToolUse, SubagentStart, SubagentStop, etc.)
- Turn spans are `agent` kind (not workflow) per spec
- Dynamic span names: session, turn, {toolName}, subagent-{type}
- Model name split from provider prefix (anthropic/claude-sonnet-4-6)
- Turn output from Stop hook's last_assistant_message
- Captures cwd, transcript_path, agent_type, is_interrupt, start_trigger
- Pure ESM package handled via import-in-the-middle with esmFirst: true
- User hooks preserved via mergeHooks (user matchers before tracer matchers)
Known gap: No LLM-level spans - the Agent SDK bundles its own Anthropic
client internally, so the existing @anthropic-ai/sdk shimmer doesn't fire.
This matches dd-trace-py's approach (agent + tool spans only).
Tests: 41 APM tracing + 13 LLM Obs tests.
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Reopening from internal branch to fix CI permissions. |
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Summary
Adds automatic instrumentation for the Claude Agent SDK (
@anthropic-ai/claude-agent-sdk), providing full visibility into agentic sessions via APM tracing and LLM Observability.Span hierarchy
Key design decisions
SessionStart,SessionEnd,Stop,PreToolUse,PostToolUse,SubagentStart,SubagentStop, etc.) — not monkey-patching internalsagentkind (notworkflow) — turns are complete agentic response cyclessession,turn,{toolName},subagent-{agentType}instead of static prefixed namesanthropic/claude-sonnet-4-6→model_name: claude-sonnet-4-6,model_provider: anthropiclast_assistant_messagefrom SDK'sStophook (the final agent text for each turn)start_trigger,project_dir,exit_reason,transcript_path,agent_type,is_interruptmergeHooks(user matchers placed before tracer matchers)import-in-the-middlewithesmFirst: trueKnown gap
No LLM-level spans — the Agent SDK bundles its own Anthropic client internally (never imports
@anthropic-ai/sdk), so the existing Anthropic shimmer doesn't fire. This matches dd-trace-py's approach: agent + tool spans only, with token metrics aggregated on the agent span fromResultMessage.Performance
~186μs overhead per session (10 spans, 22 hook invocations), ~18μs per span. Negligible vs real
query()calls.Test plan
claude-agent-sdkjob passes on Node 18 + latest