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Lark Workflow Business Advisor

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liangdabiao
lark-workflow-business-advisor

AI商业顾问团:8个AI专家角色每晚分析业务数据,汇总去重后发送编号清单到飞书,支持回复编号展开详细分析。当用户需要'商业分析'、'业务报告'、'顾问分析'、'夜间分析'、'业务建议'时使用。

Overview

Publisherliangdabiao
Repositorylark-workflow-feishu-cli
Skill namelark-workflow-business-advisor
Stars
68
Forks
10
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by liangdabiao on GitHub. Read the source before you install it.

Installation

Install the Lark Workflow Business Advisor AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/liangdabiao/lark-workflow-feishu-cli/tree/main/.claude/skills/lark-workflow-business-advisor
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/liangdabiao/lark-workflow-feishu-cli.git /tmp/lark-workflow-feishu-cli
mkdir -p .claude/skills
cp -r /tmp/lark-workflow-feishu-cli/.claude/skills/lark-workflow-business-advisor .claude/skills/lark-workflow-business-advisor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Lark Workflow Business Advisor in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Lark Workflow Business Advisor on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Lark Workflow Business Advisor is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

AI 商业顾问团工作流

CRITICAL — 开始前 MUST 先用 Read 工具读取 ../lark-shared/SKILL.md,其中包含认证、权限处理

适用场景

  • "帮我分析一下最近的业务状况" / "商业分析"
  • "生成今日业务报告" / "顾问分析"
  • "第 3 条详细说说" / "展开第 N 条建议"
  • "昨晚的分析报告" / "查看顾问建议"

前置条件

仅支持 user 身份。执行前确保已授权:

bash
lark-cli auth login --domain base,docs,im,task,calendar

本 Skill 依赖其他工作流 Skill 的数据。需要以下 Skill 至少部分初始化:

  • lark-workflow-personal-crm(CRM 联系人数据)
  • lark-workflow-social-tracker(社交媒体数据)
  • lark-workflow-content-pipeline(创意/内容数据)
  • lark-workflow-stock-analyzer(投资/财务数据)

未初始化的 Skill 数据将被跳过,不影响其他分析。

工作流总览

数据采集(每晚自动):
  ├── base +record-list (CRM) ──────► 联系人动态
  ├── base +record-list (社交追踪) ─► 数据表现
  ├── base +record-list (创意库) ───► 内容进度
  ├── base +record-list (分析记录) ─► 投资动态
  ├── task +get-my-tasks ───────────► 任务完成情况
  └── calendar +agenda ─────────────► 近期日程密度

AI 多角色分析:
  ├── 财务顾问 ──► 分析
  ├── 营销顾问 ──► 分析
  ├── 增长顾问 ──► 分析
  ├── 运营顾问 ──► 分析
  ├── 内容策略顾问 ──► 分析
  ├── 关系/BD顾问 ──► 分析
  ├── 竞争/行业顾问 ──► 分析
  └── 综合风险顾问 ──► 分析

汇总:
  AI 汇总去重排序 ──► 编号清单

输出:
  ├── doc +create ──► 存档报告
  ├── im +messages-send ──► 发送清单
  └── base +record-upsert ──► 保存分析记录

数据初始化

Base 表结构

表 1:顾问分析记录 (advisor_analysis)

字段名类型说明
分析日期日期分析执行日期
顾问角色单选财务/营销/增长/运营/内容策略/关系BD/竞争行业/综合风险
分析摘要文本该顾问的核心发现(2-3句话)
建议列表文本编号建议列表
数据来源文本使用了哪些数据源
优先级数字建议的重要性评分(1-10)

表 2:汇总建议 (advisor_summary)

字段名类型说明
建议编号文本当日编号(如 "1"、"2")
建议内容文本去重后的建议描述
来源角色文本提出该建议的顾问角色
优先级数字重要性评分
用户反馈单选未读/已读/已展开/已执行/忽略
展开详情文本用户要求展开时的详细分析
分析日期日期所属分析日期
报告链接URL当日完整报告的文档链接

初始化命令

bash
# 注意:+table-create 可能部分成功,需捕获错误后用 +field-create 补字段
# 注意:连续创建字段会触发限流(错误码 800004135),每次调用间隔至少 1 秒
lark-cli base +table-create --name "顾问分析记录" --fields '[
  {"name":"分析日期","type":"datetime"},
  {"name":"顾问角色","type":"select","multiple":false,"options":[{"name":"财务"},{"name":"营销"},{"name":"增长"},{"name":"运营"},{"name":"内容策略"},{"name":"关系BD"},{"name":"竞争行业"},{"name":"综合风险"}]},
  {"name":"分析摘要","type":"text"},
  {"name":"建议列表","type":"text"},
  {"name":"数据来源","type":"text"},
  {"name":"优先级","type":"number"}
]'
lark-cli base +table-create --name "汇总建议" --fields '[
  {"name":"建议编号","type":"text"},
  {"name":"建议内容","type":"text"},
  {"name":"来源角色","type":"text"},
  {"name":"优先级","type":"number"},
  {"name":"用户反馈","type":"select","multiple":false,"options":[{"name":"未读"},{"name":"已读"},{"name":"已展开"},{"name":"已执行"},{"name":"忽略"}]},
  {"name":"展开详情","type":"text"},
  {"name":"分析日期","type":"datetime"},
  {"name":"报告链接","type":"link"}
]'

限流处理:如果 +table-create 因限流部分失败,表仍会创建成功。此时:

  1. 用 base +table-list 获取 table_id
  2. 用 base +field-create --table-id <id> --json '{"name":"字段名","type":"text"}' 逐个补字段,每次间隔 1-2 秒

Step 1: 数据采集

根据已初始化的 Skill,拉取对应数据:

bash
# CRM 数据(如果 personal-crm 已初始化)
lark-cli base +record-list --table-id "<crm_contacts_table_id>" --filter '...热度分 < 30'
lark-cli base +record-list --table-id "<crm_interactions_table_id>" --filter '...互动时间 >= "7天前"'

# 社交追踪数据(如果 social-tracker 已初始化)
lark-cli base +record-list --table-id "<social_snapshot_table_id>" --filter '...日期 >= "7天前"'

# 创意/内容数据(如果 content-pipeline 已初始化)
lark-cli base +record-list --table-id "<idea_table_id>" --filter '...状态 != "已完成"'

# 投资数据(如果 stock-analyzer 已初始化)
lark-cli base +record-list --table-id "<portfolio_table_id>"
lark-cli base +record-list --table-id "<analysis_table_id>" --filter '...分析日期 >= "7天前"'

# 任务和日程(始终可用)
lark-cli task +get-my-tasks --page-all
lark-cli calendar +agenda --start "7天前" --end "今天"

注意:未初始化的 Skill 数据表不存在时,跳过该数据源即可,不影响其他分析。


Step 2: 8 角色独立分析

1. 财务顾问

关注数据: 投资组合(stock-analyzer)、收入/支出趋势 分析内容:

  • 投资组合表现(盈亏、波动)
  • 收入趋势变化
  • 支出是否合理
  • 现金流健康度

2. 营销顾问

关注数据: 社交媒体数据(social-tracker)、内容表现 分析内容:

  • 各平台互动趋势
  • 哪些内容类型表现最好
  • 内容发布节奏是否合理
  • 受众增长/流失趋势

3. 增长顾问

关注数据: 粉丝增长、渠道获客 分析内容:

  • 总体增长趋势
  • 增长最快/最慢的渠道
  • 增长率变化
  • 与同行的对比

4. 运营顾问

关注数据: 任务完成率、日程密度 分析内容:

  • 任务完成率(已完成/总任务)
  • 日程安排是否合理(过度/空闲)
  • 系统使用效率
  • 流程瓶颈

5. 内容策略顾问

关注数据: 创意库(content-pipeline)、内容表现 分析内容:

  • 选题质量分布
  • 创意执行进度
  • 跨平台内容效果对比
  • 内容缺口(哪些领域尚未覆盖)

6. 关系/BD 顾问

关注数据: CRM 联系人(personal-crm)、会议记录 分析内容:

  • 冷门联系人(需要跟进)
  • 新增联系人趋势
  • 关系深度分布
  • 合作机会识别

7. 竞争/行业顾问

关注数据: 知识库(knowledge-base)、行业动态 分析内容:

  • 行业趋势变化
  • 竞争对手动态
  • 新技术/新模式
  • 需要关注的新领域

8. 综合风险顾问

关注数据: 全部数据 分析内容:

  • 各维度的潜在风险
  • 薄弱环节识别
  • 需要优先处理的问题
  • 预警信号

Step 3: 汇总去重排序

AI "总秘书"角色汇总所有顾问的建议:

  1. 去重:合并不同顾问提出的相同或高度相似的建议
  2. 优先级排序:综合重要性和紧急程度
  3. 编号:为每条建议分配编号
  4. 分类标注:标注建议所属的领域

输出格式:

## 今日商业顾问团报告({日期})

### 总览
今日共收到 {N} 条独立建议,来自 {M} 位顾问。
数据来源:CRM({有/无})、社交追踪({有/无})、创意库({有/无})、投资({有/无})

### 建议清单

1. 【财务】你的投资组合本周下跌 5%,主要受科技股拖累。建议检查 AAPL 的持仓比例是否过高。
2. 【关系】张三(XX科技)已 45 天未联系,上次讨论了合作意向,建议主动跟进。
3. 【内容】本周内容发布频率下降 40%,建议安排时间完成创意库中的待执行选题。
4. 【运营】你有 7 个任务已过期未完成,其中 3 个超过 14 天,建议集中清理。
5. 【风险】竞品 YY 产品本周发布新功能,与你的产品路线图有重叠,建议关注。
...

Step 4: 发送和存档

发送到飞书

bash
lark-cli im +messages-send --chat-id "<chat_id>" --markdown "<清单内容>"

存档报告

bash
lark-cli docs +create --title "商业顾问团日报 ({日期})" --markdown "<完整报告>"

保存分析记录

bash
lark-cli base +record-upsert --table-id "<analysis_table_id>" --json '{"字段名":"值"}'
lark-cli base +record-upsert --table-id "<summary_table_id>" --json '{"字段名":"值"}'

模式二:展开详细分析

用户回复编号(如"第 3 条详细说说")时:

  1. 查找该编号对应的建议和来源角色
  2. 重新分析该角色的完整观点
  3. 提供更详细的论据和数据支持
  4. 给出具体的行动步骤

展开格式

## 第 {N} 条展开分析

### 原始建议
{原始建议内容}
### 来源顾问:{角色名}

### 详细分析
{展开的详细分析内容}

### 数据支撑
{具体数据和来源}

### 建议行动步骤
1. {步骤1}
2. {步骤2}
3. {步骤3}

### 预期效果
{如果执行该建议,预期会有什么改善}

模式三:定时执行

使用 CronCreate 设置每晚自动执行:

# 每晚 22:00 自动生成商业分析报告
CronCreate: cron="0 22 * * 1-5", prompt="运行商业顾问团分析,生成今日报告并发送到飞书", recurring=true

权限表

命令所需 scope
base +table-createbitable:app
base +record-listbitable:app:read
base +record-upsertbitable:app:write
docs +createdocx:document:create
im +messages-sendim:message:send_as_bot
task +get-my-taskstask:task:read
calendar +agendacalendar:calendar.event:read

参考

Frequently asked questions

What does the Lark Workflow Business Advisor AI skill do?

AI商业顾问团:8个AI专家角色每晚分析业务数据,汇总去重后发送编号清单到飞书,支持回复编号展开详细分析。当用户需要'商业分析'、'业务报告'、'顾问分析'、'夜间分析'、'业务建议'时使用。

Why use Lark Workflow Business Advisor on TypingMind?

Because you install it once and use it with any model. Lark Workflow Business Advisor is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Lark Workflow Business Advisor in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/liangdabiao/lark-workflow-feishu-cli/tree/main/.claude/skills/lark-workflow-business-advisor. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Lark Workflow Business Advisor?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Lark Workflow Business Advisor?

As many as you like. As long as a model supports skills, you can use Lark Workflow Business Advisor with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Lark Workflow Business Advisor AI skill free?

It is published on GitHub by liangdabiao. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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