{
    "format": "skill/v1",
    "skill_id": "legioncodeinc-honeycomb-harnesses-openclaw-skills-skill-md",
    "name": "honeycomb",
    "version": "1.0.0",
    "description": "Honeycomb persistent shared memory for the OpenClaw harness — auto-capture and recall across sessions via the local Honeycomb daemon.",
    "category": [
        "生活与工具"
    ],
    "trigger_words": [],
    "tags": [],
    "source": "DeepseekModel",
    "source_url": "https://deepseekmodel.com/skill?id=legioncodeinc-honeycomb-harnesses-openclaw-skills-skill-md",
    "exported_at": "2026-09-16T06:08:37+08:00",
    "system_prompt": "name honeycomb description Honeycomb persistent shared memory for the OpenClaw harness — auto-capture and recall across sessions via the local Honeycomb daemon. honeycomb (OpenClaw) Thin OpenClaw adapter for Honeycomb. Routes capture/recall through the local Honeycomb daemon on port 3850. No DeepLake access path ships in this bundle. Runtime tuning is supplied via openclaw.json under plugins.entries.honeycomb.config.tuning and applied by the plugin's register() into globalThis.__honeycomb_tuning__ (PRD-001b FR-7).",
    "model_config": {
        "provider": "deepseek",
        "model": "deepseek-chat",
        "temperature": 0.7,
        "max_tokens": 4096,
        "top_p": 0.9
    },
    "examples": [
        {
            "input": "请用honeycomb帮我处理问题",
            "output": "好的，我是honeycomb。Honeycomb persistent shared memory for the OpenClaw harness — auto-capture and recall across sessions via the local Honeycomb daemon. 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honeycomb，专注于生活与工具领域。Honeycomb persistent shared memory for the OpenClaw harness — auto-capture and recall across sessions via the local Honeycomb daemon."
        }
    ],
    "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"
    }
}