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Agent Skill · 研究检索

braintrust-tracing(智囊团追踪)

braintrust-tracing 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

braintrust-tracing 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证为 MIT,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 16,052。

总安装 7,417周安装 306GitHub Stars 3,663下载 2,424核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:braintrust-tracing(智囊团追踪)
来源仓库:https://github.com/parcadei/continuous-claude-v3
仓库路径:skills/braintrust-tracing
安装命令:
npx skills add https://github.com/parcadei/continuous-claude-v3 --skill braintrust-tracing
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/parcadei/continuous-claude-v3 --skill braintrust-tracing

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

braintrust-tracing 提供 Claude Code 会话在 Braintrust 中的全链路追踪指南,涵盖子代理关联与操作时序还原。适用于复杂任务根因分析、多步骤流程审计与性能调优,支持会话树形结构与 span 级细节回溯。

自动创建父会话与用户提示节点,并通过 Pre/PostToolUse 钩子捕获工具执行上下文,形成完整操作图谱。部署需配置 Braintrust SDK 与项目 tracing key,部分操作可能触发外部日志上传与身份认证流程。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/braintrust-tracing

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/parcadei/continuous-claude-v3 --skill braintru…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

braintrust-tracing 怎么安装?

在终端执行 npx skills add https://github.com/parcadei/continuous-claude-v3 --skill braintrust-tracing。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

braintrust-tracing 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

braintrust-tracing 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

braintrust-tracing 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

braintrust-tracing 用的人多吗?

公开数据是累计安装 7,417 次,近一周安装 306 次,下载 2,424 次,GitHub 3,663 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

braintrust-tracing 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 来源仓库有 3,663 星,维护活跃度相对可查。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
braintrust-tracing

智囊团追踪 · 本页

7,4173,663接触敏感数据MIT有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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

  1. 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

  1. Missing spans:

- Check current_turn_span_id in session state - Ensure Stop hook runs (turn finalization) - Look for "Failed to create" errors in log

  1. 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.

平台分布

Claude Code

27.58%
按下载量换算669

OpenCode

23.92%
按下载量换算580

Codex

19.85%
按下载量换算481

Gemini CLI

13.92%
按下载量换算337

Cursor

8.67%
按下载量换算210

windsurf

3.79%
按下载量换算92

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。

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