Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Data Analysis
Lightweight Knowledge Base
轻量级知识库与任务管理体系。结构化 JSON + MD 混合存储，支持用户画像、任务节奏、知识索引、每日自动进化。适用于中小规模记忆管理。
skill openclawclawhub Free
轻量级知识库与任务管理体系。结构化 JSON + MD 混合存储，支持用户画像、任务节奏、知识索引、每日自动进化。适用于中小规模记忆管理。
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, data/kb_index.json, data/task_rhythm.json, data/user_profile.json, references/communication.md, references/task_guidelines.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- WilliamTie
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Lightweight Knowledge Base (轻量级知识库)
轻量级知识库 + 任务管理体系 基于 V4 架构简化，采用 JSON + MD 混合存储，兼顾结构化查询与人类可读性。
核心特性
用户画像 - 结构化记录用户偏好、特质权重 任务节奏 - 每日/每周任务自动化管理 知识索引 - JSON 索引管理 MD 文件 每日进化 - 凌晨自动优化知识库 三层架构 - 宪法层 → 法规层 → 案例库
目录结构
lightweight-kb/ ├── SKILL.md # 本文件 ├── data/ │ ├── user_profile.json # 用户画像 │ ├── task_rhythm.json # 任务节奏表 │ └── kb_index.json # 知识库索引 ├── scripts/ │ ├── daily_evolve.sh # 每日进化 │ └── query.sh # 查询工具 └── references/ ├── communication.md # 沟通模式 └── task_guidelines.md # 任务执行指南
1. 初始化知识库
bash skills/lightweight-kb/scripts/init.sh 创建初始结构： data/user_profile.json - 用户画像模板 data/task_rhythm.json - 任务节奏表 data/kb_index.json - 知识库索引 memory/kb/ - 知识库目录
2. 查询用户画像
bash skills/lightweight-kb/scripts/query.sh profile "效率导向"
3. 执行每日进化
bash skills/lightweight-kb/scripts/daily_evolve.sh
宪法层 (Spec)
定义共同目标、核心原则、架构基础。 位置: lightweight-kb/SKILL.md (本文档)
法规层 (Methodology)
细分领域的执行指导。 位置: lightweight-kb/references/ 核心文件: communication.md - 沟通模式指南 task_guidelines.md - 任务执行指南
案例库 (Knowledge)
具体实例的知识库节点。 位置: memory/kb/nodes/ 示例: memory/kb/nodes/ ├── persona_xxx.json # 用户特质节点 ├── task_xxx_execution.json # 任务执行案例 └── method_xxx.json # 方法论沉淀
定时性例行任务
按固定频率执行的标准化任务。 判断特征: 频率固定（每日/每周） 产出格式稳定 执行逻辑可标准化 示例: 每日晨间简报、每周复盘
日常突发任务
用户临时提出的有一定规模的需求。 判断特征: 触发时机不固定 需要跨知识库节点协同 有一定复杂度 处理: 查用户画像 → 查历史案例 → 制定方案
日常沟通应答
即时交互、信息确认、状态查询。 判断特征: 响应即时性要求高 不产生长期文件产出 需遵循沟通风格
用户画像结构
{ "user": { "name": "老铁", "timezone": "UTC+8", "family": "沙雕之家" }, "traits": { "efficiency_oriented": 0.9, "architecture_sensitive": 0.8, "collaborative_review": 0.85, "gradual_expansion": 0.75 }, "preferences": { "communication_style": "direct_data_driven_warm", "weekly_review_day": "sunday", "deep_talk_time": "21:00" }, "knowledge_weights": { "personal_growth": 0.8, "career_development": 0.75 }, "collecting": { "interests": [], "breakthroughes": [], "value_paths": [] } }
任务节奏表结构
{ "daily": [ { "id": 1, "name": "晨间检查", "time": "08:00", "action": "check_rhythm" } ], "weekly": [ { "id": 35, "name": "综合复盘", "day": "sunday", "time": "20:00", "action": "weekly_review" }, { "id": 36, "name": "深度了解对话", "day": "sunday", "time": "21:00", "action": "deep_dialogue" } ] }
凌晨 1:00 自动执行
更新知识图谱 - 合并新记忆 任务节奏检查 - 验证一致性 方法论沉淀 - 从案例提取模式 用户画像更新 - 更新特质权重
执行脚本
bash skills/lightweight-kb/scripts/daily_evolve.sh
基础原则
直接、理性、数据驱动 增加人性化表达和温暖语气 不展示内部思考过程 聚焦结论与建议
文件沟通
当需要展示结构化信息时： 使用清晰的标题层级 提供选项需灵活（1-5条不等） 信息引导自然融入对话流
文件目录规则
目录用途outputs/晨间简报、健康报告等核心交付资产temp/过程数据与缓存src/逻辑脚本与工具data/结构化数据（JSON）memory/kb/知识库与锚点
注意事项
Spec 维护纪律 - 日常沟通禁改 SKILL.md，仅在明确要求时修改 紧急记录 - 需先报备，经认可后安排即时任务 信息采集 - 遵循自然对话流，优先在固定场景嵌入
相关技能
memory-manager - 基础记忆管理（MD 文件） kokoro-tts - 语音合成 feishu-message - 飞书消息
Category context
Data access, storage, extraction, analysis, reporting, and insight generation.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
3 Docs3 Config
- SKILL.md
- references/communication.md
- references/task_guidelines.md
- data/kb_index.json
- data/task_rhythm.json
- data/user_profile.json