跳到正文
cccskills
免费在 GitHub 公开

braintrust-tracing

Inspect Claude Code execution traces in Braintrust, including tool calls and token usage. The guide explains event hooks, troubleshooting missing records, and matching separate parent and sub-agent traces using timestamps and metadata.

中文简介正在准备中。当前显示英语简介。

原文查看原文说明

Braintrust tracing for Claude Code - hook architecture, sub-agent correlation, debugging

查看安装方法

适用场景

  • Investigating missing execution traces
  • Reviewing tool calls and token usage
  • Matching parent and sub-agent execution records
  • Exporting traces for agent run datasets

包含的文件(1)

  • SKILL.md12.6 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Braintrust Tracing for Claude Code

Comprehensive guide to tracing Claude Code sessions in Braintrust, including sub-agent correlation.

Architecture Overview

                         PARENT SESSION
                    +---------------------+
                    |  SessionStart       |
                    |  (creates root)     |
                    +----------+----------+
                               |
                    +----------v----------+
                    |  UserPromptSubmit   |
                    |  (creates Turn)     |
                    +----------+----------+
                               |
          +--------------------+--------------------+
          |                    |                    |
+---------v--------+  +--------v--------+  +--------v--------+
| PostToolUse      |  | PostToolUse     |  | PreToolUse      |
| (Read span)      |  | (Edit span)     |  | (Task - inject) |
+------------------+  +-----------------+  +--------+--------+
                                                    |
                                         +----------v----------+
                                         |   SUB-AGENT         |
                                         |   SessionStart      |
                                         |   (NEW root_span_id)|
                                         +----------+----------+
                                                    |
                                         +----------v----------+
                                         |   SubagentStop      |
                                         |   (has session_id)  |
                                         +---------------------+

Hook Event Flow

HookTriggerCreatesKey Fields
SessionStartSession beginsRoot spansession_id, root_span_id
UserPromptSubmitUser sends promptTurn spanprompt, turn_number
PreToolUseBefore tool runs(modifies Task prompts)tool_input.prompt
PostToolUseAfter tool runsTool spantool_name, input, output
StopTurn completesLLM spansmodel, tokens, tool_calls
SubagentStopSub-agent finishes(no span)session_id of sub-agent
SessionEndSession ends(finalizes root)turn_count, tool_count

Trace Hierarchy

Session (task span) - root_span_id = session_id
|
+-- Turn 1 (task span)
|   |
|   +-- claude-sonnet (llm span) - model call with tool_use
|   +-- Read (tool span)
|   +-- Edit (tool span)
|   +-- claude-sonnet (llm span) - response after tools
|
+-- Turn 2 (task span)
|   |
|   +-- claude-sonnet (llm span)
|   +-- Task (tool span) -----> [Sub-agent session - SEPARATE trace]
|   +-- claude-sonnet (llm span)
|
+-- Turn 3 ...

Sub-Agent Tracing: What Works and What Doesn't

What Doesn't Work

SessionStart doesn't receive the Task prompt.

We tried injecting trace context into Task prompts via PreToolUse:

# PreToolUse hook injects:
[BRAINTRUST_TRACE_CONTEXT]
{"root_span_id": "abc", "parent_span_id": "xyz", "project_id": "123"}
[/BRAINTRUST_TRACE_CONTEXT]

But SessionStart only receives session metadata, not the modified prompt. The injected context is lost.

What DOES Work

Task spans in parent session contain everything:

  • agentId - identifier for the sub-agent run
  • totalTokens, totalToolUseCount - metrics
  • content - full agent response/summary
  • tool_input.prompt - original task prompt
  • tool_input.subagent_type - agent type (e.g., "oracle")

SubagentStop hook receives the sub-agent's session_id:

  • This equals the sub-agent's orphaned trace root_span_id
  • Allows correlation between parent Task span and child trace

The Correlation Pattern

Current state: Sub-agents create orphaned traces (new root_span_id).

Correlation method:

  1. Query parent session's Task spans for agent metadata
  2. Match agentId or timing with orphaned traces
  3. Sub-agent's session_id = its trace's root_span_id

Future solution (not yet implemented):

SubagentStop fires -> writes session_id to temp file
PostToolUse (Task) -> reads temp file -> adds child_session_id to Task span metadata

This would link: Task.agentId + Task.child_session_id -> orphaned trace root_span_id

State Management

Per-Session State Files

~/.claude/state/braintrust_sessions/
  {session_id}.json       # Per-session state

Each session file contains:

{
  "root_span_id": "abc-123",
  "project_id": "proj-456",
  "turn_count": 5,
  "tool_count": 23,
  "current_turn_span_id": "turn-789",
  "current_turn_start": 1703456789,
  "started": "2025-12-24T10:00:00.000Z",
  "is_subagent": false
}

Global State

~/.claude/state/braintrust_global.json   # Cached project_id
~/.claude/state/braintrust_hook.log      # Debug log

Debugging Commands

Check if Tracing is Active

# View hook logs in real-time
tail -f ~/.claude/state/braintrust_hook.log

# Check if session has state
cat ~/.claude/state/braintrust_sessions/*.json | jq -s '.'

# Verify environment
echo "TRACE_TO_BRAINTRUST=$TRACE_TO_BRAINTRUST"
echo "BRAINTRUST_API_KEY=${BRAINTRUST_API_KEY:+set}"

Query Braintrust Directly

# List recent sessions
uv run python -m runtime.harness scripts/braintrust_analyze.py --sessions 5

# Analyze last session
uv run python -m runtime.harness scripts/braintrust_analyze.py --last-session

# Replay specific session
uv run python -m runtime.harness scripts/braintrust_analyze.py --replay <session-id>

# Find sub-agent traces (orphaned roots)
uv run python -m runtime.harness scripts/braintrust_analyze.py --agent-stats

Debug Hook Execution

# Enable verbose logging
export BRAINTRUST_CC_DEBUG=true

# Test hooks manually
echo '{"session_id":"test-123","type":"resume"}' | \
  bash "$CLAUDE_PROJECT_DIR/.claude/plugins/braintrust-tracing/hooks/session_start.sh"

# Test PreToolUse (Task injection)
echo '{"session_id":"test-123","tool_name":"Task","tool_input":{"prompt":"test"}}' | \
  bash "$CLAUDE_PROJECT_DIR/.claude/plugins/braintrust-tracing/hooks/pre_tool_use.sh"

Troubleshooting Checklist

  1. No traces appearing:

    • Check TRACE_TO_BRAINTRUST=true in .claude/settings.local.json
    • Verify API key: echo $BRAINTRUST_API_KEY
    • Check logs: tail -20 ~/.claude/state/braintrust_hook.log
  2. Sub-agents not linking:

    • This is expected - sub-agents create orphaned traces
    • Use --agent-stats to find agent activity
    • Correlate via timing or agentId in parent Task span
  3. Missing spans:

    • Check current_turn_span_id in session state
    • Ensure Stop hook runs (turn finalization)
    • Look for "Failed to create" errors in log
  4. State corruption:

    • Remove session state: rm ~/.claude/state/braintrust_sessions/*.json
    • Clear global cache: rm ~/.claude/state/braintrust_global.json

Key Files

FilePurpose
.claude/plugins/braintrust-tracing/hooks/common.shShared utilities, API, state management
.claude/plugins/braintrust-tracing/hooks/session_start.shCreates root span, handles sub-agent context
.claude/plugins/braintrust-tracing/hooks/user_prompt_submit.shCreates Turn spans per user message
.claude/plugins/braintrust-tracing/hooks/pre_tool_use.shInjects trace context into Task prompts
.claude/plugins/braintrust-tracing/hooks/post_tool_use.shCreates tool spans, captures agent/skill metadata
.claude/plugins/braintrust-tracing/hooks/stop_hook.shCreates LLM spans, finalizes Turns
.claude/plugins/braintrust-tracing/hooks/session_end.shFinalizes session, triggers learning extraction
scripts/braintrust_analyze.pyQuery and analyze traced sessions
~/.claude/state/braintrust_sessions/Per-session state files
~/.claude/state/braintrust_hook.logDebug log

Environment Variables

VariableRequiredDefaultDescription
TRACE_TO_BRAINTRUSTYes-Set to "true" to enable
BRAINTRUST_API_KEYYes-API key for Braintrust
BRAINTRUST_CC_PROJECTNoclaude-codeProject name
BRAINTRUST_CC_DEBUGNofalseVerbose logging
BRAINTRUST_API_URLNohttps://api.braintrust.devAPI endpoint

Session Learnings

What We Learned About Sub-Agent Tracing (Dec 2025)

Attempted: Inject trace context via PreToolUse into Task prompts.

Result: Failed - SessionStart only receives session metadata, not the prompt.

Discovery: Task spans already contain rich sub-agent data:

  • metadata.agent_type - agent type from subagent_type
  • metadata.skill_name - skill from Skill tool
  • tool_input - full prompt sent to agent
  • tool_output - agent response

Current correlation path:

  1. Parent session Task span has agentId and timing
  2. Sub-agent creates orphaned trace with root_span_id = session_id
  3. SubagentStop provides the sub-agent's session_id
  4. Manual correlation: match timing or use session_id link

Future work: Write child_session_id to Task span metadata from PostToolUse after SubagentStop.

What We Learned About Sub-Agent Correlation

The Problem

  • Sub-agents spawned via Task tool create orphaned Braintrust traces
  • Parent session has Task spans with agentId, sub-agent has separate session_id
  • No built-in link between them

What DOESN'T Work

1. Prompt injection via PreToolUse

SessionStart hook only receives session metadata (session_id, type, cwd), NOT the prompt. Injected trace context is never seen.

The hook receives:

{
  "session_id": "...",
  "type": "start|resume|compact|clear",
  "cwd": "...",
  "env": {...}
}

No prompt field exists - context injection is impossible at SessionStart.

2. SubagentStop → PostToolUse file handoff

Race condition. These are independent async hooks with no timing guarantees:

  • SubagentStop fires when sub-agent session ends
  • PostToolUse (Task) fires when Task tool completes
  • No ordering guarantee between them
  • Writing to a correlation file creates a race

3. PreToolUse correlation files

SessionStart can't access the task_span_id because it has no context about which Task spawned it. PreToolUse modifies prompts but doesn't create a reliably accessible state file that SessionStart can find.

What DOES Work

Post-hoc matching for dataset building:

Parent session Task spans contain:

  • agentId - identifier for the sub-agent run
  • totalTokens, totalToolUseCount - aggregated metrics
  • content - full agent response/summary
  • tool_input.prompt - original task prompt
  • tool_input.subagent_type - agent type (e.g., "oracle")
  • Start/end timestamps

Sub-agent sessions contain:

  • session_id (equals orphaned trace root_span_id)
  • Start/end timestamps
  • All internal spans and tool calls

Correlation strategy:

  1. Export parent session traces (query parent root_span_id)
  2. Export sub-agent traces (query all sessions created within parent's time window)
  3. Match by:
    • Timing: Task span end ≈ sub-agent session end
    • Metadata: subagent_type from Task prompt
    • IDs: SubagentStop hook provides session_id (can be captured and logged)

Architecture Insight

SessionStart input is intentionally minimal - it contains no prompt or tool context:

interface SessionStartInput {
  session_id: string;
  type: "start" | "resume" | "compact" | "clear";
  cwd: string;
  env: { [key: string]: string };
  // NO: prompt, tool_context, task_span_id, parent_span_id
}

This design boundary prevents real-time correlation at hook time.

Recommendation

For building agent run datasets with sub-agent correlation:

  1. In-session logging: Capture SubagentStop session_id in logs or state
  2. Post-session export: Query Braintrust API for parent and sub-agent traces
  3. Offline correlation: Match traces by timing and metadata in a script
  4. Don't try real-time linking: Hooks don't have necessary context

Example script pattern:

# 1. Export parent session
braintrust_analyze.py --replay <parent-session-id> > parent_traces.json

# 2. Query for orphaned sub-agent traces (those created during parent's time window)
braintrust_analyze.py --agent-stats > all_agent_traces.json

# 3. Correlate in Python:
#    - Parent Task spans -> agentId, timestamps, subagent_type
#    - Orphaned traces -> root_span_id, timestamps
#    - Match by timing and type

This approach is reliable, testable, and doesn't require hooks to maintain implicit state.

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Coordinate background agents through saved files, keeping lengthy work transcripts out of the main conversation. It defines how to pass results between agents, monitor progress, and verify completed work with tests.

中文简介正在准备中。当前显示英语简介。

  • Keeping long agent transcripts out of the main conversation
  • Passing research and plans between agents through files
  • Checking for stalled background agents
parcadei/Continuous-Claude-v339462026年1月27日 更新

Delegate implementation, file reading, and testing to separate agents, then bring concise summaries back to the main conversation. The rules explain when delegation helps and when a small edit is better handled directly.

中文简介正在准备中。当前显示英语简介。

  • Implementing a feature across multiple files
  • Completing a specific phase of an implementation plan
  • Delegating feature development and testing
parcadei/Continuous-Claude-v339462026年1月27日 更新

Organize implementation work across research, planning, validation, implementation, and review agents. Each stage passes files to the next, while implementation starts with failing tests and the main conversation coordinates the workflow.

中文简介正在准备中。当前显示英语简介。

  • Dividing implementation work among specialized agents
  • Checking a plan against research before implementation
  • Writing failing tests before implementing changes
parcadei/Continuous-Claude-v339462026年1月27日 更新

Connect Agentica SDK agents to Claude Code CLI through a proxy, an intermediary server. Use setup and debugging guidance to address file permissions, streamed responses, result formatting, and agents reporting success without performing the requested operations.

中文简介正在准备中。当前显示英语简介。

  • Connecting Agentica agents to Claude Code tools
  • Investigating file write and edit permission errors
  • Debugging streaming and REPL response formats
parcadei/Continuous-Claude-v339462026年1月27日 更新

Consult Agentica APIs when building workflows where multiple AI agents cooperate. This reference covers eleven coordination patterns, agent tracking, shared state, handoffs, and ways to combine results, with pointers to detailed API specifications.

中文简介正在准备中。当前显示英语简介。

  • Choose a coordination pattern for multiple agents
  • Check pattern constructors and methods
  • Implement custom coordination patterns
parcadei/Continuous-Claude-v339462026年1月27日 更新

Write clearer instructions for Agentica and REPL agents by specifying roles, file operations, and output formats. Includes templates for dividing research, coordinating specialists, reviewing solutions, and passing results between agents through files.

中文简介正在准备中。当前显示英语简介。

  • Clarifying instructions for reading and editing files
  • Dividing research among multiple agents
  • Passing findings and plans between agents
parcadei/Continuous-Claude-v339462026年1月27日 更新

查看 parcadei 的全部技能

报告此技能的问题