使用提示:本仓库所含 skill 文件均由用户在 WorkBuddy 平台官方渠道、通过自己个人账号、以普通对话方式生成。未使用破解安装包 / 获取应用文件夹内文件 / 反编译 / 抓包 / 模型 API 调用数据逆向等技术手段。不保证与 WorkBuddy 原版 100% 一致(平台侧可能更新,生成结果受 prompt / 模型版本影响)。
本仓库存档 WorkBuddy 平台(一个 AI 协作专家 agent 市场)的团队协作型 skill —— 每个 folder 对应一个"专家团"(多角色协作的 agent 集合),包含一个主理人 + 多个专业角色,工作流化地完成特定场景任务(投资研究 / 视频制作 / MVP 开发 / 财税 / 法务 / 营销 / 设计 / 法律 / 数据分析 等)。
Skill 内容主要由两类来源组装而成:
- WorkBuddy 官方团队(在 WorkBuddy 账号标记为 "WorkBuddy 团队")
- 特邀作者 / 合作方(Easychen / 卡尔的AI沃茨 / 花叔 (Alchain) / 苍何 / 杜哥学量化 / 百望股份 / vincentlli / Excellent / AI科学局 / Xu Qingchu 等)
每个 skill 在导入 orchestration 框架(OpenAI Custom GPTs / Claude Project / Coze / Dify / MetaGPT / AutoGen / CrewAI 等)时相当于一份长 system prompt,可以整体调度主理人 → 使用子 agent 调用成员,完成复杂的多阶段协作。
代码 / 文档部分采用 MIT 许可证(详见 LICENSE 文件)。
- 生成方式透明。所有 skill 文件均由用户在 WorkBuddy 平台官方渠道、通过自己的个人账号、以普通对话方式生成。未使用破解安装包、未获取应用文件夹内文件、未反编译、未抓包、未基于模型 API 调用数据逆向等任何技术手段。
- 不保证一致性。skill 内容在不同时间 / 不同 prompt / 不同模型版本下可能会有细微差异,因此不保证与 WorkBuddy 原版 100% 一致。如你依赖其中任何信息(法条、财税规则、投资建议、医疗/安全关键内容),请务必自行核实。
- 数据与合规。生成素材来自:合法的 WorkBuddy 平台调用输出、领域合规文档、公开语料。用户对自己在本仓下载 / 使用的内容负全部责任。
- 第三方 attribution。部分 skill 直接复用了下列开源 / 特邀作者的方法论或文档,版权与归属仍属原作者:
- 一人企业方法论(One Person Company):Easychen — https://github.com/easychen/opc-methodology
- AST-based Humanize PPT(MIT License):LearnPrompt 团队 — https://github.com/LearnPrompt/humanize-ppt
- 腾讯自选股股票投研系列:作者
jensonli@tencent.com - "刺桐说 Pro" 投资社群系列:杜哥学量化
- "卡尔的人感 PPT" 系列:卡尔的AI沃茨
- "AI 视频创作 / 视频解剖" 系列:苍何
- "花叔数据分析" 系列:花叔 (Alchain)
- "智能发票" 系列:百望股份
- "Makers 开发" 系列:vincentlli
- "MVP 开发" 系列:Excellent
- "NCRE 等级考试" 系列:Xu Qingchu
- "KET 备考" 系列:AI科学局
如你为原始作者且希望修改或移除相关内容,请开 Issue — 我们会在 5 个工作日内响应。
📖 阅读建议:找到你关心的类别 → 点开对应目录 → 优先看
README.md(没有 README 的以SKILL.md或主理人*-team-lead.md为准)。 一个 skill 可能出现在多个类别(如seo-content-skills同时属于"内容营销"与"SEO"),下表按主类别只列一次,在"复用视角"段指出跨域协作。
| 新目录 | 简介 | 专家数(主理人 + 成员) |
|---|---|---|
investment-masters-skills |
AI 式对冲基金圆桌 — 13 位传奇投资哲学家 + 6 位分析师 + 2 位管理人(投资组合经理 + 风控师),参考巴菲特 / 芒格 / 费雪 / 邓普顿 / 达利欧 / ・拉什・库马尔等 | 21 |
a-share-skills |
A 股全链路研究:宏观策略 → 产业映射 → 资金追踪 → 个股深度 → 估值 → 风险诊断 → 投顾 | 8 |
stock-partner-skills |
腾讯自选股实战派:产业策略 / 信号捕捉 / 估值 / 抄底 / 基本面 / 短线,6 大真实炒股视角 | 7 |
trading-agent-skills |
多空辩论式投研:技术面 / 基本面 / 新闻 / 情绪 / 多空研究员 / 研究总监 / 交易员 / 三方风险 | 13 |
citongshuopro-skills |
刺桐说 Pro 投资社群:主理人调度 4 位社群嘉宾(Gy / 贾总 / 小星 / 张老师) | 4 |
super-partner-skills |
福帮手超级合伙人:入口路由 → 公司下一步 / 天才合伙人 / 多维度协同工作坊 / 服务跟进 / 乐包商业化 | 11 |
| 新目录 | 复用场景 |
|---|---|
content-monetization-skills |
CPS 带货 / CPE·CPM 效果广告 / 创作者 ↔ 品牌交易撮合 / BD — 5 人商业化闭环 |
super-partner-skills |
商业化落地:乐包激活与能力继续(Lebao),把能力调用转成商业计划 |
a-share-skills / stock-partner-skills |
A 股 / 投研内容→ 个人 IP 素材 |
investment-masters-skills |
大师方法论(dhandho-master 等)→ 付费课程 / 知识产品 |
| 新目录 | 简介 | 专家数 |
|---|---|---|
ai-content-creator-skills |
多模态内容生产:创意策略 / 文案 / 影像生成 / 精修合成 / 素材改编 / AI 视频 | 7+ |
video-gen-skills |
AI 短视频团队:采集(灵阅)→ 策划脚本(灵枢)→ 渲染 MP4(灵映)+ 引用素材库 | 5 |
promo-creator-skills |
产品宣传片:创意简报 → 逐镜头分镜 → 素材生产 → HyperFrames 剪辑 → BGM → 交付 | 6 |
content-distribution-skills |
跨 13+ 平台多平台分发(含微信视频号、小红书) | 5 |
marketing-campaign-skills |
营销战役:内容创作 / 活动策划 / SEO / 品牌分析 — 4 人全生命周期 | 4 |
seo-content-skills |
SEO 内容营销:关键词研究 / 技术优化 / 长文创作 / 内容编辑 / 链接策略 / 转化率分析 | 5+ |
ket-prep-skills |
KET 剑桥少儿备考:学情诊断 / 词汇语法 / 听读 / 写说 / 模考 | 5 |
ncre-exam-skills |
NCRE 计算机等级:一级→四级 + 主理人(徐庆初) | 5 |
open-spec-doc-skills |
企业级长文档:调研 / 生成 / 审核 — 6 阶段 SOP | 3 |
humanize-ppt-skills |
AST 人感 PPT:大纲导演 → 魁藏 / Zara / HyperFrames / OPC / 前端 HTML / 视频动效 | 5+ |
| 新目录 | 简介 | 专家数 |
|---|---|---|
academic-journal-selector-skills |
学术选刊顾问 v3.0:中外刊并行管道,冲稳保三层投稿方案 | 4 |
gpt-researcher-skills |
深度研究:5 阶段 SOP,多源聚合 + 审稿循环 | 6 |
ket-prep-skills |
同上(语言教学复用) | — |
ncre-exam-skills |
同上(考试复用) | — |
| 新目录 | 简介 | 专家数 |
|---|---|---|
aicoding-architecture-expert-skills |
复杂系统架构:摄入→调研→高层→系统→UserStory→部署→安全 + Gate 返工 | 6 |
mvp-dev-skills |
MVP 全栈:PM / 设计 / 架构 / 前端 / 后端 / QA / DevOps | 7 |
makers-skills |
EdgeOne Makers 部署:前端 / 后端 / AI Agent / CLI / 部署 + 交付总监 | 6 |
software-company-skills |
软件公司(快速模式):PM 定需求 → 架构师拆任务 → 工程师批量实现 → QA | 5 |
software-workshop |
GStack 软件工坊:产品评审 / 代码审查 / 安全审计 / QA / 设计系统 / 调试运维 + 主理人 | 6 |
engineering-assurance-skills |
工程保障:架构评审 / 代码审查 / SRE 事故响应 / 测试 / 技术文档 | 5 |
ai-data-copilot-skills |
智数分析 (Crew AI):SQL / 数据科学 / RAG / 可视化 / 报告生成 | 6 |
| 新目录 | 简介 | 专家数 |
|---|---|---|
design-engine-skills |
设计原型:发现 / 设计系统 / 原型 / 评审 / 导出 + 主理人 + 内置 71 套设计系统 | 6 |
humanize-ppt-skills |
(见 3.3)AST 方法论上游,作为设计工程的一支 | — |
| 新目录 | 简介 | 专家数 |
|---|---|---|
chatlaw-skills |
中文法律咨询:民事 / 婚姻 / 合同 / 劳动 / 侵权 — 4 阶段 + 判例撰写 | 5 |
enterprise-legal-skills |
企业法务:合同 / 并购 / 劳动 / 隐私 / 产品 / 合规 / AI 治理 / IP + 中国区本地化 | 9 |
smb-team-skills |
SMB 经营总管:客户 / 合约 / 投诉 / CRM / 流失预警 | 1 |
| 新目录 | 简介 | 专家数 |
|---|---|---|
tax-compliance-skills |
财税合规:票据 / 记账 / 报表 / 税务申报 / 合规审计 + 主理人 + 引擎 | 6 |
invoice-verify-skills |
智能发票(百望体系):识别 → 验真 → 征信 → 归档 | 5 |
| 新目录 | 简介 | 专家数 |
|---|---|---|
huashu-data-pro-skills |
花叔本地数据分析:趋势 / 结构 / 异常三专家并行,网页 / Excel / PPT 三格式报告 | 3+ |
ai-data-copilot-skills |
智数分析(应用化 SQL 工作流,侧重应用系统落地) | — |
| 新目录 | 简介 | 专家数 |
|---|---|---|
sales-battle-skills |
销售攻坚:客户研究 / 竞品情报 / 外联策略 / 销售预测 — 主理人 + 4 成员 | 5 |
| 新目录 | 简介 | 专家数 |
|---|---|---|
hr-operations-skills |
HR 运营:招聘 / 薪酬分析 / 组织发展 / 入职管理 + 主理人 | 5 |
| 新目录 | 简介 | 专家数 |
|---|---|---|
social-engagement-skills |
社媒增长:AI 评论 / 互动自动化 / 品牌舆情 / 信号挖掘 — 覆盖 14+ 平台 | 5 |
| 新目录 | 简介 | 专家数 |
|---|---|---|
product-strategy-skills |
产品战略:需求 / 用户研究 / 竞品 / 数据 / 路线图 + 主理人 | 5 |
gpt-researcher-skills |
(见 3.4,深度研究复用) | — |
每个 SKILL.md 本质上是一段长 system prompt。典型用法:
- 直接用作 OpenAI Custom GPTs / Claude Project / Gemini / Coze / Dify / MetaGPT / AutoGen / CrewAI 的 system prompt
- 把"知识检索工具"调用改成目标平台的等价工具即可跨框架移植
- 最优结构:以
*team-lead/SKILL.md作为 orchestrator,成员 skill 按需作子 agent 调用
本仓统一改为 kebab-case-skills 风格:
| 原 WorkBuddy 团队名 | 仓内目录 |
|---|---|
| InvestmentGroups | investment-masters-skills |
| TradingAgentTeam | trading-agent-skills |
| AiContentCreatorTeam | ai-content-creator-skills |
| AiDataCopilot | ai-data-copilot-skills |
| DesignEngineTeam | design-engine-skills |
| 刺桐说Pro | citongshuopro-skills |
| 学术选刊顾问团 | academic-journal-selector-skills |
| 社媒互动增长专家团 | social-engagement-skills |
| 花叔数据分析专家团 | huashu-data-pro-skills |
| StockPartnerTeam | stock-partner-skills |
| GPTResearcherTeam | gpt-researcher-skills |
| SeoContentTeam | seo-content-skills |
| MvpDevExpertTeam | mvp-dev-skills |
| … | … |
完整对照表请查看附录 A。
本仓 skill 不强制依赖其他目录,但一些 skill 在 description: 段提到协作场景:
mvp-dev-skills↔makers-skills↔aicoding-architecture-expert-skills:前端 / 后端 / Agent 提示注入的工程互参marketing-campaign-skills↔seo-content-skills:共享关键词策略 / 内容日历模板product-strategy-skills下游可接到ai-data-copilot-skills/huashu-data-pro-skillschatlaw-skills↔enterprise-legal-skills↔smb-team-skills:消费者 ↔ 企业 ↔ SMB 三层法律阶梯investment-masters-skills/a-share-skills/trading-agent-skills三套投研互相 roundtable
| 目标 | 选用 |
|---|---|
| 营销 + 内容 | ai-content-creator-skills + content-distribution-skills + marketing-campaign-skills |
| A 股投研 | a-share-skills + stock-partner-skills + trading-agent-skills |
| 大师圆桌 | investment-masters-skills |
| MVP / App 交付 | mvp-dev-skills 或 mvp-dev-skills + software-company-skills |
| 设计 → 工程闭环 | design-engine-skills + software-company-skills + software-workshop |
| 数据 / 分析策略 | ai-data-copilot-skills + huashu-data-pro-skills |
| 内容变现 | content-monetization-skills + promo-creator-skills |
| 学术 / 教育 / 选刊 | academic-journal-selector-skills + gpt-researcher-skills + ket-prep-skills + ncre-exam-skills |
| SMB 经营治理 | enterprise-legal-skills + tax-compliance-skills + invoice-verify-skills + hr-operations-skills + smb-team-skills |
| 投研 IP 变现 | stock-partner-skills + investment-masters-skills + citongshuopro-skills |
欢迎任何能提高 skill 复用性 / 团队互操作性 / 可读性 / 可移植性 的贡献。
- 事实修复:若
SKILL.md内容已与目录不一致 → 开 PR / Issue - 翻译:任何尚未有
README.en.md的 skill → 欢迎补英译 - SOP 模板化:把跨 skill 的 lead 检查单 / member 返工契约 / Gate 清单提出
_templates/ - 框架迁移:把 WorkBuddy 原生工具调用移植到 LangChain / CrewAI / AutoGen / Dify,放在
examples/ - 保留原作者 attribution:衍生 README 顶部保留原始作者 ID / 链接 /
name:字段
- PR 正文列出:涉及哪些目录、新增哪些模板、移除了哪些硬编码工具调用。
- 禁止提交商业账号 id / token、API key 等敏感信息。
- 如补
README.en.md,请与README.zh.md的章节号一致。
| 旧目录名(迁移前) | 新目录名 |
|---|---|
| InvestmentGroups | investment-masters-skills |
| SEOskills | seo-content-skills |
| aicoding-expert-team | aicoding-architecture-expert-skills |
| content-distribution-team | content-distribution-skills |
| copilot-skills | ai-data-copilot-skills |
| doc-team-skills | open-spec-doc-skills |
| engineering-assurance | engineering-assurance-skills |
| hr-operations-skill-files | hr-operations-skills |
| invoice-verify-skill-docs | invoice-verify-skills |
| ket | ket-prep-skills |
| marketing-campaign | marketing-campaign-skills |
| ncre-skills | ncre-exam-skills |
| opc-team-docs | opc-team-skills |
| product-strategy | product-strategy-skills |
| research-team-skills | gpt-researcher-skills |
| sales-battle | sales-battle-skills |
| smb-skills | smb-team-skills |
| stock-partner-skill-docs | stock-partner-skills |
| video-gen-team-skills | video-gen-skills |
| 刺桐说Pro | citongshuopro-skills |
| 学术选刊顾问团 | academic-journal-selector-skills |
| 社媒互动增长专家团 | social-engagement-skills |
| 花叔数据分析专家团 | huashu-data-pro-skills |
- 39 个 skill 目录
- 450+ 个 md 文档(SKILL.md / README.md / agents / members / references)
- 13 个一级分类、~170+ 个独立专家角色
- 总仓库大小:~600KB 纯文本(平台描述性 skill 包,无模型权重)
你不需要写代码,也能把这份 repo 里的许多 expert skills 立刻用在日常对话 AI 上。
核心思路:任何一个 SKILL.md 本质都是一段很长很详细的「系统提示词」;把它们粘贴到对话中,就相当于「召唤了那个专家」。
| App | How to use | Good for |
|---|---|---|
| Doubao (豆包, ByteDance) | ① Go to "智能体 / AI 应用" → "创建智能体" ② Paste a SKILL.md into the "系统提示词" (system prompt)③ Keep trigger words as sample prompts in instructions |
Copywriting / marketing / content / office / education |
| DeepSeek (深度求索) | ① Paste the full SKILL.md at the start of the conversation or as a 【系统消息】② Multi-turn conversations will adhere to the SOP |
Investment research / documents / data analysis / code |
| Kimi (月之暗面) | Same as above; Kimi supports long system prompts well | Long documents / legal / journal selection |
| Tongyi Qianwen (通义千问, Alibaba) | ① "创作" → "创建智能体" ② Paste as main system prompt |
E-commerce copy / marketing / office |
| ERNIE Bot (文心一言, Baidu) | Paste in prompt mode; no deployment needed | Education / everyday Q&A |
| Tencent Yuanbao (腾讯元宝) | Paste as system prompt and start chatting | GPT apps / investment research |
| App | How to use | Good for |
|---|---|---|
| ChatGPT (free tier) | Paste SKILL.md at the very beginning of the conversation |
General |
| Gemini (Google) | Use "Custom Instructions" or prepend with "system:" in the message | General / office |
| Claude.ai (Anthropic) | Project → System Prompt → paste the full SKILL.md |
Copywriting / policy / serious content |
| HuggingChat | Any open-weight Chinese-friendly model accepts long system prompts | General |
| Poe (Quora) | Bot settings → System Prompt | General |
- Pick a skill, e.g.
chatlaw-skills (中文法律咨询团). - Open https://github.com/darker2016/workbuddy-skill-groups/tree/main/chatlaw-skills.
- Copy the full text of each file:
chatlaw-info-intake.md,chatlaw-legal-research.md,chatlaw-case-precedent.md,chatlaw-advice-writer.md,chatlaw-report-finalizer.md. - Create a new "智能体" in Doubao and paste the 5 blocks as one long system prompt.
- Send a legal query — you will get an analysis close to what WorkBuddy produces natively.
If you try these skills outside WorkBuddy and the result feels weaker, that is usually expected. Please calibrate your expectations:
- Sub-agent dispatch is flattened. On WorkBuddy each member is an "independently scheduled agent"; in a free app you have to compress all member rules into a single conversation context. Complex tasks with many hand-offs easily lose context inside a single thread.
- Tool calls cannot be executed natively. Many skills depend on WorkBuddy tool-calls (knowledge retrieval / private data sources). On these free apps those tools do not exist, so the skill "downgrades" to a guidance prompt.
- Cross-session memory & RAG are missing. WorkBuddy maintains session-level memory and document-level RAG; a single conversation on other apps cannot share complex context across stages.
- Role consistency drifts on very long tasks. With long prompts and many turns, the model tends to "forget which stage it is on and who should be acting".
Recommended for:
- One-shot / short flows (< 10 turns in a single session)
- Skills dominated by one lead role (e.g. copywriting, legal advice, learning diagnosis)
- "Use the lead's SKILL.md as a high quality system prompt" scenarios
Not recommended for:
- Tasks that require many agents working in parallel (e.g. 13 philosopher-investors producing simultaneous independent output in
investment-masters-skills) - Tasks that depend on WorkBuddy private data sources / live financial data
- Very long multi-phase collaborations (e.g. 6-stage MVP development in
mvp-dev-skills)
Best practice: in these free apps, try using only the lead's SKILL.md as the system prompt and insert member output/input as samples or on demand — this is the most stable approach. For serious or high-stakes conclusions, please use the skills directly on WorkBuddy.
最后,想手打一段对 WorkBuddy 团队的感谢。
我们刚才所做的所有工作 — 把平台上用过的专家团 skills 复刻成开源仓库 — 全部是通过普通对话方式、在 WorkBuddy 官方渠道、用我们自己的个人账号生成的。过程中没有使用破解安装包、没有获取应用文件夹内的文件、没有反编译、没有抓包、没有基于模型 API 调用数据逆向。
但与此同时,我们也发现 WorkBuddy 团队非常开放:对这些 skills,官方没有藏着掖着,对照后发现应用内的系统提示词几乎没有限制、屏蔽、混淆等动作。换句话说,如果你是一个愿意花时间认真描述需求 + 善于提问的人,完全可以在 WorkBuddy 上"对话式生成"出近乎完美的专有 agent skill —— 这是 WorkBuddy 作为产品最值得被看见的地方。
Everything we did above — re-creating the expert-team skills we had used on the platform as this open-source repo — was generated through ordinary text conversations on the official WorkBuddy channel, using our own personal accounts. At no point did we use cracked installers, extract bundled app files, reverse engineer, packet-sniff, or reconstruct outputs from model API calls.
Along the way we also discovered that the WorkBuddy team is genuinely open: for these skills, the official app hid nothing; comparing inputs and outputs showed that the in-app system prompts contain almost no obfuscation, no masking, no deliberate redaction. In other words: if you are someone willing to spend time describing your needs carefully and asking good questions, you can "author-by-dialogue" a near-perfect proprietary agent skill entirely on WorkBuddy — and that is the most compelling thing about WorkBuddy as a product.
Usage notice: All skill files in this repo are generated by end users through ordinary text conversations with the official WorkBuddy platform using their own personal accounts. No cracked installers, no extraction of bundled app files, no reverse engineering, no packet sniffing, and no reverse-engineering by model-API-call data — none of these technical means were employed. No guarantee that these skills are 100% identical to the WorkBuddy originals (the platform may update; outputs depend on prompt / model version).
This repo archives multi-agent collaboration skills from WorkBuddy — an "AI expert agent marketplace". Each subfolder is an "expert team" (one orchestrator + multiple specialist roles), designed to complete stage-based work in a specific domain:
- Investment research, monetization & trading
- Content creation, video production, marketing & distribution
- Design, MVP development, DevOps, legal, tax, sales, HR, data analysis
- Academic prep, exam prep, social-media growth, journal selection
Each skill can be imported into any agent / orchestration framework (OpenAI Custom GPTs / Claude Project / Gemini / Coze / Dify / MetaGPT / AutoGen / CrewAI etc.) as a long system prompt. Loading *team-lead/SKILL.md as orchestrator and invoking member skills as on-demand sub-agents is the canonical way to use them.
Code and docs are released under MIT License (see LICENSE).
- Transparent generation. Every skill file is generated by the end user through ordinary conversation with the WorkBuddy official platform under their own personal account. No cracked installers; no extraction of bundled app files; no reverse engineering; no packet sniffing; no reconstruction from model API call data.
- No identity guarantee. Skill content can vary slightly across time / prompts / model versions; no guarantee of 100% fidelity to the WorkBuddy originals. Always independently verify any information you rely on here (legal clauses, tax rules, investment advice, medical / safety-critical content).
- Data & compliance. Generation material comes from legitimate WorkBuddy platform calls, in-domain compliance documents, or public corpora. You are solely responsible for how you use the contents of this repo.
- Third-party attribution. Some skills directly reuse methodologies or documentation from the following open-source / guest authors — copyright and attribution remain with the original authors:
- One Person Company Methodology: Easychen — https://github.com/easychen/opc-methodology
- AST-based Humanize PPT (MIT License): LearnPrompt team — https://github.com/LearnPrompt/humanize-ppt
- Tencent Stock Partner series: author
jensonli@tencent.com - Citongshuopro Investment Community: DuGeLearnQuant (杜哥学量化)
- Carl's Human-like PPT: Carl AI Watts (卡尔的AI沃茨)
- AI Video Creation & Video Dissection: Cang He (苍何)
- HuaShu Data Analysis: HuaShu (花叔 / Alchain)
- Smart Invoice series: BaiWang Group (百望股份)
- Makers Dev series: vincentlli
- MVP Dev series: Excellent
- NCRE Exam prep series: Xu Qingchu
- KET Exam prep series: AI Science Bureau (AI科学局)
If you are an original author and wish to have your content modified or removed, please open an Issue — we will respond within 5 business days.
📖 Reading tip: Find your category → open the folder → start with
README.md; if absent, read the team-lead'sSKILL.mdor*-team-lead.md. A skill can appear in multiple categories; this table lists each skill only once under its primary category with cross-links in section 4.
| Folder | Short description | Experts (lead + members) |
|---|---|---|
investment-masters-skills |
AI hedge-fund roundtable — 13 legendary philosophers + 6 analysts + 2 managers (portfolio + risk); reference Buffett / Munger / Fisher / Templeton / Dalio / Jhunjhunwala | 21 |
a-share-skills |
A-share end-to-end: macro → industry → capital flow → single-name → valuation → risk-diagnosis → advisor | 8 |
stock-partner-skills |
Tencent Stock Partner real-trader cases: industry strategy / signal capture / valuation / bottom-fishing / fundamentals / short-term | 7 |
trading-agent-skills |
Bull-bear debate investing: technical / fundamental / news / sentiment / bull & bear researchers / research director / trader / three-way risk | 13 |
citongshuopro-skills |
Citongshuopro investment community: lead routes 4 community guests (Gy / Jia / LittleStar / ZhangLaoshi) | 4 |
super-partner-skills |
FuBangShou Super Partner: entry routing → "company next step" / genius-draft / multi-workshop / service-follow / Lebao commercialization | 11 |
| Folder | Reuse scenario |
|---|---|
content-monetization-skills |
CPS affiliate / CPE·CPM ads / creator↔brand match / BD sales — 5-person monetization loop |
super-partner-skills |
Commercialization landing: Lebao activation & capability continuation |
a-share-skills / stock-partner-skills |
A-share / investment-research content → personal-IP material |
investment-masters-skills |
Master methodologies (dhandho-master etc.) → paid courses / knowledge products |
| Folder | Short description | Experts |
|---|---|---|
ai-content-creator-skills |
Multimedia content production: creative strategy / copywriting / video-gen / image-gen / retouching / adaptation / AI video | 7+ |
video-gen-skills |
AI short-video team: collector / planner·scriptwriter / producer·renderer + reference lib | 5 |
promo-creator-skills |
Product promo videos: brief → storyboard → asset → HyperFrames edit → BGM → delivery | 6 |
content-distribution-skills |
13+ cross-platform distribution (incl. WeChat video, Xiaohongshu) | 5 |
marketing-campaign-skills |
Marketing campaign: content creator / planner / SEO / brand analyst — 4-person full lifecycle | 4 |
seo-content-skills |
SEO content marketing: keyword research / tech SEO / long-form / editing / link strategy / CRO | 5+ |
ket-prep-skills |
Cambridge KET prep: aptitude / vocab+grammar / listening+reading / speaking+writing / mock | 5 |
ncre-exam-skills |
NCRE computer ranks: Level 1→4 + lead (Xu Qingchu) | 5 |
open-spec-doc-skills |
Enterprise long-docs: research → generate → review — 6-stage SOP | 3 |
humanize-ppt-skills |
AST human-like PPT: outline director → Kuizang / Zara / HyperFrames / OPC / front-end HTML / Remotion video | 5+ |
| Folder | Short description | Experts |
|---|---|---|
academic-journal-selector-skills |
Academic journal selector v3.0: parallel CN/EN pipelines, tiered submission | 4 |
gpt-researcher-skills |
Deep research: 5-stage SOP with multi-source aggregation + review loop | 6 |
ket-prep-skills |
Ditto (language teaching reuse) | — |
ncre-exam-skills |
Ditto (exam reuse) | — |
| Folder | Short description | Experts |
|---|---|---|
aicoding-architecture-expert-skills |
Complex-system architecture: intake → research → high-level → system → UserStory → deploy → security + Gate-based rework | 6 |
mvp-dev-skills |
MVP full-stack: PM / designer / architect / frontend / backend / QA / DevOps | 7 |
makers-skills |
EdgeOne Makers deployment: frontend / backend / AI Agent / CLI / deploy + delivery director | 6 |
software-company-skills |
Software company (fast mode): PM specs → architect splits → engineer batch-implements → QA | 5 |
software-workshop |
GStack Software Workshop: product review / code review / security audit / QA / design system / ops | 6 |
engineering-assurance-skills |
Engineering assurance: architecture review / code review / SRE incident / testing / tech-writing | 5 |
ai-data-copilot-skills |
Crew AI (智数分析): SQL / data science / RAG / visualization / report composer | 6 |
| Folder | Short description | Experts |
|---|---|---|
design-engine-skills |
Design-prototype: discovery / design-system / prototype / review / export + lead + 71 built-in design systems | 6 |
humanize-ppt-skills |
(see 3.3) AST methodology upstream of design engineering | — |
| Folder | Short description | Experts |
|---|---|---|
chatlaw-skills |
Chinese legal advisory: civil / marriage / contract / labor / tort — 4-stage SOP + case writing | 5 |
enterprise-legal-skills |
Enterprise legal: commercial / M&A / labor / privacy / product / compliance / AI governance / IP + 2 CN-localized packs | 9 |
smb-team-skills |
SMB governance: customer / contract / complaints / CRM / churn | 1 |
| Folder | Short description | Experts |
|---|---|---|
tax-compliance-skills |
Tax compliance: invoicing / bookkeeping / reporting / filing / audit + lead + engine | 6 |
invoice-verify-skills |
Smart Invoice (BaiWang series): recognize → verify → credit-check → archive | 5 |
| Folder | Short description | Experts |
|---|---|---|
huashu-data-pro-skills |
HuaShu local analytics: trend / structure / anomaly trio, HTML / Excel / PPT triple-report, data stays local | 3+ |
ai-data-copilot-skills |
智数分析 (application-focussed SQL workflow) | — |
| Folder | Short description | Experts |
|---|---|---|
sales-battle-skills |
Sales force: account research / competitive intel / outreach / forecast · lead + 4 members | 5 |
| Folder | Short description | Experts |
|---|---|---|
hr-operations-skills |
HR operations: recruiting / comp / org-development / onboarding + lead | 5 |
| Folder | Short description | Experts |
|---|---|---|
social-engagement-skills |
Social-media growth: AI comments / interaction automation / brand monitoring / signal mining — covers 14+ platforms | 5 |
| Folder | Short description | Experts |
|---|---|---|
product-strategy-skills |
Product strategy: requirement / user-research / competitive / data / roadmap + lead | 5 |
gpt-researcher-skills |
(see 3.4, deep research reuse) | — |
Each SKILL.md is effectively a long system prompt. To use it:
- Drop directly as the system prompt for OpenAI Custom GPTs / Claude Project / Gemini / Coze / Dify / MetaGPT / AutoGen / CrewAI.
- Rewrite only the knowledge-retrieval tool calls to port across frameworks.
- Best practice: load
*team-lead/SKILL.mdas orchestrator and invoke member skills on demand as sub-agents.
This repo is normalized to kebab-case-skills style. Full old → new mapping in Appendix A.
Skills in this repo do not hard-depend on other folders, but a few reference collaboration scenarios in their description::
mvp-dev-skills↔makers-skills↔aicoding-architecture-expert-skills: shared front/back/agent prompt-injection engineeringmarketing-campaign-skills↔seo-content-skills: shared keyword-strategy & content-calendar templateproduct-strategy-skillsdownstream feedsai-data-copilot-skills/huashu-data-pro-skillschatlaw-skills↔enterprise-legal-skills↔smb-team-skills: 3-tier legal ladder (consumer ↔ enterprise ↔ SMB)investment-masters-skills/a-share-skills/trading-agent-skills: cross-roundtable investment analysis
| Goal | Start with |
|---|---|
| Marketing & content | ai-content-creator-skills + content-distribution-skills + marketing-campaign-skills |
| A-share equity research | a-share-skills + stock-partner-skills + trading-agent-skills |
| Multi-master roundtable | investment-masters-skills |
| MVP / app delivery | mvp-dev-skills or mvp-dev-skills + software-company-skills |
| Design-dev closed loop | design-engine-skills + software-company-skills + software-workshop |
| Data / analytics strategy | ai-data-copilot-skills + huashu-data-pro-skills |
| Content monetization | content-monetization-skills + promo-creator-skills |
| Academic / EdTech / journal selection | academic-journal-selector-skills + gpt-researcher-skills + ket-prep-skills + ncre-exam-skills |
| SMB governance | enterprise-legal-skills + tax-compliance-skills + invoice-verify-skills + hr-operations-skills + smb-team-skills |
| Investment IP monetization | stock-partner-skills + investment-masters-skills + citongshuopro-skills |
Contributions are welcome as long as they improve skill reusability / team interoperability / readability / portability.
- Factual fixes: if a
SKILL.mdno longer matches its folder → PR / Issue - Translations: any skill without
README.en.mdis open for translation - SOP templating: extract the recurring lead checklists, member rework contracts, and Gate checklists into
_templates/ - Framework migration: port any WorkBuddy-native tool-call into LangChain / CrewAI / AutoGen / Dify minimal demos under
examples/ - Author attribution: keep the original author IDs / links /
name:fields at the top of derived READMEs.
- PR body lists: affected folders, new templates, hardcoded tool calls removed.
- Never commit commercial account ids or tokens.
- If adding
README.en.md, mirror section numbering withREADME.zh.md.
| Old directory (before reorganization) | New directory |
|---|---|
| InvestmentGroups | investment-masters-skills |
| SEOskills | seo-content-skills |
| aicoding-expert-team | aicoding-architecture-expert-skills |
| content-distribution-team | content-distribution-skills |
| copilot-skills | ai-data-copilot-skills |
| doc-team-skills | open-spec-doc-skills |
| engineering-assurance | engineering-assurance-skills |
| hr-operations-skill-files | hr-operations-skills |
| invoice-verify-skill-docs | invoice-verify-skills |
| ket | ket-prep-skills |
| marketing-campaign | marketing-campaign-skills |
| ncre-skills | ncre-exam-skills |
| opc-team-docs | opc-team-skills |
| product-strategy | product-strategy-skills |
| research-team-skills | gpt-researcher-skills |
| sales-battle | sales-battle-skills |
| smb-skills | smb-team-skills |
| stock-partner-skill-docs | stock-partner-skills |
| video-gen-team-skills | video-gen-skills |
| 刺桐说Pro | citongshuopro-skills |
| 学术选刊顾问团 | academic-journal-selector-skills |
| 社媒互动增长专家团 | social-engagement-skills |
| 花叔数据分析专家团 | huashu-data-pro-skills |
- 39 skill directories
- 450+ md files (SKILL.md / README.md / agents / members / references)
- 13 top-level categories, ~170+ distinct expert roles
- Total repo size: ~600KB text only (no model weights).
You do not need to write any code to start using many of the skills from this repo in your favorite chat AI today.
Core idea: every SKILL.md is, in essence, a long and detailed system prompt; paste it into a conversation and you have effectively "summoned that expert".
| App | How to use | Good for |
|---|---|---|
| Doubao (豆包, ByteDance) | ① Go to "智能体 / AI 应用" → "创建智能体" ② Paste a SKILL.md into the "系统提示词" (system prompt)③ Keep trigger words as sample prompts in instructions |
Copywriting / marketing / content / office / education |
| DeepSeek (深度求索) | ① Paste the full SKILL.md at the start of the conversation or as a 【系统消息】② Multi-turn conversations will adhere to the SOP |
Investment research / documents / data analysis / code |
| Kimi (月之暗面) | Same as above; Kimi supports long system prompts well | Long documents / legal / journal selection |
| Tongyi Qianwen (通义千问, Alibaba) | ① "创作" → "创建智能体" ② Paste as main system prompt |
E-commerce copy / marketing / office |
| ERNIE Bot (文心一言, Baidu) | Paste in prompt mode; no deployment needed | Education / everyday Q&A |
| Tencent Yuanbao (腾讯元宝) | Paste as system prompt and start chatting | GPT apps / investment research |
| App | How to use | Good for |
|---|---|---|
| ChatGPT (free tier) | Paste SKILL.md at the very beginning of the conversation |
General |
| Gemini (Google) | Use "Custom Instructions" or prepend with "system:" in the message | General / office |
| Claude.ai (Anthropic) | Project → System Prompt → paste the full SKILL.md |
Copywriting / policy / serious content |
| HuggingChat | Any open-weight Chinese-friendly model accepts long system prompts | General |
| Poe (Quora) | Bot settings → System Prompt | General |
- Pick a skill, e.g.
chatlaw-skills (中文法律咨询团). - Open https://github.com/darker2016/workbuddy-skill-groups/tree/main/chatlaw-skills.
- Copy the full text of each file:
chatlaw-info-intake.md,chatlaw-legal-research.md,chatlaw-case-precedent.md,chatlaw-advice-writer.md,chatlaw-report-finalizer.md. - Create a new "智能体" in Doubao and paste the 5 blocks as one long system prompt.
- Send a legal query — you will get an analysis close to what WorkBuddy produces natively.
If you try these skills outside WorkBuddy and the result feels weaker, that is usually expected. Please calibrate your expectations:
- Sub-agent dispatch is flattened. On WorkBuddy each member is an "independently scheduled agent"; in a free app you have to compress all member rules into a single conversation context. Complex tasks with many hand-offs easily lose context inside a single thread.
- Tool calls cannot be executed natively. Many skills depend on WorkBuddy tool-calls (knowledge retrieval / private data sources). On these free apps those tools do not exist, so the skill "downgrades" to a guidance prompt.
- Cross-session memory & RAG are missing. WorkBuddy maintains session-level memory and document-level RAG; a single conversation on other apps cannot share complex context across stages.
- Role consistency drifts on very long tasks. With long prompts and many turns, the model tends to "forget which stage it is on and who should be acting".
Recommended for:
- One-shot / short flows (< 10 turns in a single session)
- Skills dominated by one lead role (e.g. copywriting, legal advice, learning diagnosis)
- "Use the lead's SKILL.md as a high quality system prompt" scenarios
Not recommended for:
- Tasks that require many agents working in parallel (e.g. 13 philosopher-investors producing simultaneous independent output in
investment-masters-skills) - Tasks that depend on WorkBuddy private data sources / live financial data
- Very long multi-phase collaborations (e.g. 6-stage MVP development in
mvp-dev-skills)
Best practice: in these free apps, try using only the lead's SKILL.md as the system prompt and insert member output/input as samples or on demand — this is the most stable approach. For serious or high-stakes conclusions, please use the skills directly on WorkBuddy.
最后,想手打一段对 WorkBuddy 团队的感谢。
我们刚才所做的所有工作 — 把平台上用过的专家团 skills 复刻成开源仓库 — 全部是通过普通对话方式、在 WorkBuddy 官方渠道、用我们自己的个人账号生成的。过程中没有使用破解安装包、没有获取应用文件夹内的文件、没有反编译、没有抓包、没有基于模型 API 调用数据逆向。
但与此同时,我们也发现 WorkBuddy 团队非常开放:对这些 skills,官方没有藏着掖着,对照后发现应用内的系统提示词几乎没有限制、屏蔽、混淆等动作。换句话说,如果你是一个愿意花时间认真描述需求 + 善于提问的人,完全可以在 WorkBuddy 上"对话式生成"出近乎完美的专有 agent skill —— 这是 WorkBuddy 作为产品最值得被看见的地方。
Everything we did above — re-creating the expert-team skills we had used on the platform as this open-source repo — was generated through ordinary text conversations on the official WorkBuddy channel, using our own personal accounts. At no point did we use cracked installers, extract bundled app files, reverse engineer, packet-sniff, or reconstruct outputs from model API calls.
Along the way we also discovered that the WorkBuddy team is genuinely open: for these skills, the official app hid nothing; comparing inputs and outputs showed that the in-app system prompts contain almost no obfuscation, no masking, no deliberate redaction. In other words: if you are someone willing to spend time describing your needs carefully and asking good questions, you can "author-by-dialogue" a near-perfect proprietary agent skill entirely on WorkBuddy — and that is the most compelling thing about WorkBuddy as a product.