{
    "format": "skillpro/v1",
    "skill_id": "linuxhsj-openclaw-zero-token-skills-session-logs-skill-md",
    "name": "session-logs",
    "version": "1.0.0",
    "description": "Search and analyze your own session logs (older/parent conversations) using jq.",
    "category": [
        "人际情感"
    ],
    "trigger_words": [],
    "tags": [],
    "source": "DeepseekModel",
    "source_url": "https://deepseekmodel.com/skill?id=linuxhsj-openclaw-zero-token-skills-session-logs-skill-md",
    "exported_at": "2026-09-16T21:51:58+08:00",
    "system_prompt": "name session-logs description Search and analyze your own session logs (older/parent conversations) using jq. metadata {\"openclaw\":{\"emoji\":\"📜\",\"requires\":{\"bins\":\"[Truncated]\"}}} 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. 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 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 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'",
    "model_config": {
        "provider": "deepseek",
        "model": "deepseek-chat",
        "temperature": 0.7,
        "max_tokens": 4096,
        "top_p": 0.9
    },
    "examples": [
        {
            "input": "请用session-logs帮我处理问题",
            "output": "好的，我是session-logs。Search and analyze your own session logs (older/parent conversations) using jq. 我会根据你的需求提供专业帮助。"
        },
        {
            "input": "介绍一下你的能力",
            "output": "我是session-logs，专注于人际情感领域。Search and analyze your own session logs (older/parent conversations) using jq."
        }
    ],
    "install_guide": {
        "coze": "在 Coze 平台创建 Bot -> 技能配置 -> 导入此 .skill 文件",
        "dify": "在 Dify 平台创建应用 -> 添加知识库 -> 导入此 .skill 配置",
        "claude": "将 system_prompt 字段内容复制到 Claude 自定义指令中",
        "custom": "将此 .skill 文件加载到你的 AI Agent 框架中，解析 system_prompt 和 model_config 即可使用"
    },
    "scripts": {
        "python": "# session-logs - Python extension\n# Add custom Python logic here\ndef process(input_data):\n    return input_data\n",
        "javascript": "// session-logs - JavaScript extension\n// Add custom JS logic here\nfunction process(inputData) {\n    return inputData;\n}\n"
    },
    "tools": {
        "mcp_servers": [],
        "api_endpoints": []
    },
    "dependencies": {
        "python": [],
        "node": []
    },
    "hooks": {
        "on_load": "echo \"Skill loaded: session-logs\"",
        "on_call": "",
        "on_error": "echo \"Skill error: please check logs\""
    }
}