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clawtraceclawtrace 分析

Agent Skill

clawtrace 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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。

总安装

3,192

周安装

133

GitHub Stars

公开资料未说明

下载量

1,064
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:clawtrace(clawtrace 分析)
来源仓库:https://github.com/leoluo0814/clawtrace
安装命令:
openclaw skills install clawtrace
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。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install clawtrace

简介

clawtrace 用于单会话日志跟踪与调试,帮助分析 OpenClaw 对话细节。

  • 适用于排查响应异常、关联上下文或审查历史操作记录。
  • 自动提取当前会话 ID 并匹配本地日志文件进行可视化展示。
  • 安装前需确保日志级别已设为 debug 以便捕获详细信息。
  • 建议定期归档日志,防止磁盘空间被长期占用。clawtrace 属于效率类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
claw-trace
description
Trace and debug a single OpenClaw conversation session. Use when you need to analyze openclaw logs, correlate them with the current session context, inspect workflow steps, summarize module activity, or produce a structured trace report.

ClawTrace

ClawTrace analyzes one OpenClaw session at a time. It combines OpenClaw logs and current session context to reconstruct steps, summarize module activity, and generate a Markdown trace report.

When to Use

  • Inspect one OpenClaw session end to end
  • Explain slow, failed, retried, or noisy runs
  • Generate a structured session trace report
  • Produce evidence-based optimization suggestions

Core Rules

  1. Always analyze one session at a time.
  2. Always use both data sources before writing the report:

- openclaw logs --json --local-time --no-color - current session context

  1. Never invent missing values. Use Not available, Estimated, or Unknown when needed.
  2. Prefer exact identifiers and timestamps over inferred values.
  3. Write the report in the user's language unless the user asks for another language.
  4. If the user's chat channel supports file sending, prefer delivering the report as a Markdown file; otherwise reply directly in chat using the same report structure.
  5. Do not output raw logs, raw JSON, or verbatim log lines in the final report.

Inputs

Logs

Use JSON logs so events can be parsed reliably.

openclaw logs --json --local-time --no-color
  • --limit <n> to restrict line count
  • --max-bytes <n> to avoid huge tails
  • --interval <ms> if polling is needed
  • --timeout <ms> if waiting for fresh output
  • --expect-final only when the task requires waiting for the final response

Context

Use current session context to identify the target run and recover information not explicit in logs, such as request scope, recent responses, session clues, and context-size indicators.

Analysis Workflow

1: Identify the Target Session

  • sessionId
  • sessionKey
  • runId
  • channel
  • nearby timestamps
  • current-session clues

If multiple runs exist in the same session, prefer the latest completed run unless the user clearly points to a different one.

2: Extract Key Events

Extract session, prompt, agent, tool, lane, context, warning, error, and related gateway events, and capture the key fields needed for analysis such as time, level, module, sessionID, runID, tool, toolCallID, duration, summary, and outcome.

3: Reconstruct Steps

Convert events into ordered steps such as queue, prompt, agent, tool, gateway, context, warn, error, and done.

When possible, pair start and end events to compute duration. If only one side exists, mark duration as Unknown.

4: Compute Metrics

  • Session ID
  • Session Key
  • Run ID
  • Start and End Time
  • Total Duration
  • Step Count
  • Tool Count
  • Warning Count
  • Error Count
  • Module Count
  • Context Indicators
  • Token Indicators

Use exact values when present. Otherwise mark them as Estimated or Not available.

5: Produce Optimization Suggestions

Only give evidence-based suggestions, such as duplicate tool calls, oversized context, repeated warnings, long tool durations, queue delays, or excessive gateway noise.

If there is no clear optimization opportunity, say that no evidence-backed optimization was found.

Output Format

If file sending is supported in the user's chat channel, prefer a Markdown file such as clawtrace-run-<runId>.md or clawtrace-report-<timestamp>.md; otherwise return the same structure directly in chat.

Example Markdown output:

# ClawTrace Report

## Overview
Scope: RunId=<runId> or Message=<message>
Start: <start>
End: <end>
Total Tokens Used: <tokens>
Total Duration: <total_duration> (seconds)
Total Steps: <steps_count> 
Tools Used: <tools_list> (separated by comma)
Warnings: <warn_count>
Errors: <error_count>
Generated at: <time>

Suggestions:
- <evidence-based suggestion>
- <evidence-based suggestion>

## Modules

| Module | Success | Warn | Error | Total Steps | Avg Time Cost | Notes |
| --- | ---: | ---: | ---: | ---: | --- | --- |
| <module> | <success> | <warn> | <error> | <total_steps> | <avg_time_cost> | <notes> |

## Steps

| Step | Time | Type | Module | Action | Duration | Result | Notes |
| ---: | --- | --- | --- | --- | --- | --- | --- |
| 1 | <time> | <type> | <module> | <action> | <duration> | <result> | <notes> |
| 2 | <time> | <type> | <module> | <action> | <duration> | <result> | <notes> |

Sort the Steps table strictly by time in ascending order. Use Success, Failed, Warning, or Unknown for Result, and do not include raw logs or raw JSON.

Partial Data

If the logs contain Log tail truncated (increase --max-bytes)., explicitly state that the report is based on partial logs.

Do not fabricate missing steps. Mark uncertain durations and metrics as Unknown, Estimated, or Not available.

Noise Filtering

Ignore unrelated background noise such as cron timers, heartbeats, and unrelated channel traffic unless they materially affect the target session.

Quality Standard

The report should quickly show which session was analyzed, how long it took, what modules and steps were involved, where time went, what warnings or failures happened, and what to optimize next. If evidence is weak, say so clearly.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

80.67%
按下载量换算858

安全审计

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ClawScan

通过

Static analysis

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权限和风险

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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