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openclaw-session-log-forensicsOpenClaw session LOG forensics 搜索

Agent Skill

openclaw-session-log-forensics 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

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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:openclaw-session-log-forensics(OpenClaw session LOG forensics 搜索)
来源仓库:https://github.com/danielsinewe/openclaw-session-log-forensics
安装命令:
openclaw skills install openclaw-session-log-forensics
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 openclaw-session-log-forensics

简介

使用 jq + rg 分析 OpenClaw 会话 JSONL 历史记录以了解成本峰值、工具调用异常和行为回归。

SKILL.md

name
session-logs
description
Analyze OpenClaw session JSONL history for cost spikes, tool-call anomalies, and behavior regressions with jq + rg.
metadata
{ "openclaw": { "emoji": "📜", "requires": { "bins": ["jq", "rg"] } } }

session-logs

Search your complete conversation history stored in session JSONL files. Use this when a user references older/parent conversations or asks what was said before.

This fork is tuned for OpenClaw operators who need fast incident forensics (cost spikes, tool-call drift, and behavior regressions) across many sessions.

Trigger

Use this skill when the user asks about prior chats, parent conversations, or historical context that isn't in memory files.

Location

Session logs live at: ~/.openclaw/agents/<agentId>/sessions/ (use the agent=<id> value from the system prompt Runtime line).

  • sessions.json - Index mapping session keys to session IDs
  • <session-id>.jsonl - Full conversation transcript per session

Structure

Each .jsonl file contains messages with:

  • type: "session" (metadata) or "message"
  • timestamp: ISO timestamp
  • message.role: "user", "assistant", or "toolResult"
  • message.content[]: Text, thinking, or tool calls (filter type=="text" for human-readable content)
  • message.usage.cost.total: Cost per response

Common Queries

List all sessions by date and size

for f in ~/.openclaw/agents/<agentId>/sessions/*.jsonl; do
  date=$(head -1 "$f" | jq -r '.timestamp' | cut -dT -f1)
  size=$(ls -lh "$f" | awk '{print $5}')
  echo "$date $size $(basename $f)"
done | sort -r

Find sessions from a specific day

for f in ~/.openclaw/agents/<agentId>/sessions/*.jsonl; do
  head -1 "$f" | jq -r '.timestamp' | grep -q "2026-01-06" && echo "$f"
done

Extract user messages from a session

jq -r 'select(.message.role == "user") | .message.content[]? | select(.type == "text") | .text' <session>.jsonl

Search for keyword in assistant responses

jq -r 'select(.message.role == "assistant") | .message.content[]? | select(.type == "text") | .text' <session>.jsonl | rg -i "keyword"

Get total cost for a session

jq -s '[.[] | .message.usage.cost.total // 0] | add' <session>.jsonl

Daily cost summary

for f in ~/.openclaw/agents/<agentId>/sessions/*.jsonl; do
  date=$(head -1 "$f" | jq -r '.timestamp' | cut -dT -f1)
  cost=$(jq -s '[.[] | .message.usage.cost.total // 0] | add' "$f")
  echo "$date $cost"
done | awk '{a[$1]+=$2} END {for(d in a) print d, "$"a[d]}' | sort -r

Count messages and tokens in a session

jq -s '{
  messages: length,
  user: [.[] | select(.message.role == "user")] | length,
  assistant: [.[] | select(.message.role == "assistant")] | length,
  first: .[0].timestamp,
  last: .[-1].timestamp
}' <session>.jsonl

Tool usage breakdown

jq -r '.message.content[]? | select(.type == "toolCall") | .name' <session>.jsonl | sort | uniq -c | sort -rn

Daily tool-call volume (find sudden jumps)

for f in ~/.openclaw/agents/<agentId>/sessions/*.jsonl; do
  date=$(head -1 "$f" | jq -r '.timestamp' | cut -dT -f1)
  calls=$(jq -r '.message.content[]? | select(.type=="toolCall") | .name' "$f" | wc -l | tr -d ' ')
  echo "$date $calls"
done | awk '{a[$1]+=$2} END {for(d in a) print d, a[d]}' | sort

Cost outlier scan (quick anomaly triage)

for f in ~/.openclaw/agents/<agentId>/sessions/*.jsonl; do
  sid=$(basename "$f" .jsonl)
  cost=$(jq -s '[.[] | .message.usage.cost.total // 0] | add' "$f")
  echo "$sid $cost"
done | sort -k2,2nr | head -20

Threshold anomaly flagger (cost or tool-call spikes)

COST_THRESHOLD=2
CALL_THRESHOLD=40
for f in ~/.openclaw/agents/<agentId>/sessions/*.jsonl; do
  sid=$(basename "$f" .jsonl)
  cost=$(jq -s '[.[] | .message.usage.cost.total // 0] | add' "$f")
  calls=$(jq -r '.message.content[]? | select(.type=="toolCall") | .name' "$f" | wc -l | tr -d ' ')
  if awk "BEGIN {exit !($cost > $COST_THRESHOLD || $calls > $CALL_THRESHOLD)}"; then
    printf "%s cost=%s tool_calls=%s\
" "$sid" "$cost" "$calls"
  fi
done | sort -t= -k2,2nr

Set COST_THRESHOLD and CALL_THRESHOLD from your baseline, then run this after incidents to immediately shortlist suspicious sessions.

Compare two sessions (message mix regression)

for s in <old-session>.jsonl <new-session>.jsonl; do
  echo "== $s =="
  jq -s '{
    total: length,
    user: ([.[] | select(.message.role=="user")] | length),
    assistant: ([.[] | select(.message.role=="assistant")] | length),
    tool_calls: ([.[] | .message.content[]? | select(.type=="toolCall")] | length),
    total_cost: ([.[] | .message.usage.cost.total // 0] | add)
  }' "$s"
done

Compact forensic snapshot for one session

jq -s '
  def tool_names: [.[] | .message.content[]? | select(.type=="toolCall") | .name];
  {
    session_id: (input_filename | split("/")[-1] | sub("\\.jsonl$"; "")),
    first: .[0].timestamp,
    last: .[-1].timestamp,
    messages: length,
    user_msgs: ([.[] | select(.message.role=="user")] | length),
    assistant_msgs: ([.[] | select(.message.role=="assistant")] | length),
    tool_calls: (tool_names | length),
    top_tools: (
      tool_names
      | group_by(.)
      | map({name: .[0], count: length})
      | sort_by(-.count)
      | .[:5]
    ),
    total_cost: ([.[] | .message.usage.cost.total // 0] | add)
  }
' <session>.jsonl

Use this when you need a fast "what changed?" summary to share in incident notes.

Search across ALL sessions for a phrase

rg -l "phrase" ~/.openclaw/agents/<agentId>/sessions/*.jsonl

Tips

  • Sessions are append-only JSONL (one JSON object per line)
  • Large sessions can be several MB - use head/tail for sampling
  • The sessions.json index maps chat providers (discord, whatsapp, etc.) to session IDs
  • Deleted sessions have .deleted.<timestamp> suffix
  • Keep one baseline "healthy" session id around to compare against regressions quickly.

Fast text-only hint (low noise)

jq -r 'select(.type=="message") | .message.content[]? | select(.type=="text") | .text' ~/.openclaw/agents/<agentId>/sessions/<id>.jsonl | rg 'keyword'

适合场景

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用户想查找某类 Agent Skill 时

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需要根据任务场景推荐可安装能力包时

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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

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能力 2

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能力 3

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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。

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该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

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