account-research by anthropics/knowledge-work-plugins
npx skills add https://github.com/anthropics/knowledge-work-plugins --skill account-research在接触前全面了解任何公司或个人。此技能始终与网络搜索配合使用,结合数据增强和 CRM 数据后效果显著提升。
┌─────────────────────────────────────────────────────────────────┐
│ 客户调研 │
├─────────────────────────────────────────────────────────────────┤
│ 始终可用(通过网页搜索独立工作) │
│ ✓ 公司概览:业务内容、规模、行业 │
│ ✓ 近期新闻:融资、领导层变动、公告 │
│ ✓ 招聘信号:开放职位、增长指标 │
│ ✓ 关键人物:来自 LinkedIn 的领导团队 │
│ ✓ 产品/服务:销售内容、服务对象 │
├─────────────────────────────────────────────────────────────────┤
│ 超级增强(连接您的工具后) │
│ + 数据增强:已验证邮箱、电话、技术栈、组织架构图 │
│ + CRM:过往关系、历史商机、联系人 │
└─────────────────────────────────────────────────────────────────┘
只需告诉我需要调研的对象:
我会立即进行网络搜索。如果您连接了数据增强或 CRM 工具,我也会获取相关数据。
广告位招租
在这里展示您的产品或服务
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连接您的工具以增强此技能:
| 连接器 | 新增功能 |
|---|---|
| 数据增强 | 已验证邮箱、电话号码、技术栈、组织架构图、融资详情 |
| CRM | 过往关系历史、历史商机、现有联系人、备注 |
没有连接器? 没关系。网络搜索可以为任何公司或个人提供扎实的调研信息。
# 调研报告:[公司或个人名称]
**生成时间:** [日期]
**数据来源:** 网络搜索 [+ 数据增强] [+ CRM]
---
## 快速概览
[2-3 句话:他们是谁,为什么可能需要您,最佳接触角度]
---
## 公司档案
| 字段 | 值 |
|-------|-------|
| **公司** | [名称] |
| **网站** | [URL] |
| **行业** | [行业] |
| **规模** | [员工数量] |
| **总部** | [地点] |
| **成立时间** | [年份] |
| **融资情况** | [阶段 + 金额(如已知)] |
| **营收** | [估算值(如有)] |
### 业务内容
[1-2 句话描述其业务、产品和客户]
### 近期新闻
- **[标题]** — [日期] — [对您接触的重要性]
- **[标题]** — [日期] — [重要性说明]
### 招聘信号
- [X] [部门] 的开放职位
- 值得注意:[相关职位,如工程、销售、AI/ML]
- 增长指标:[招聘速度解读]
---
## 关键人物
### [姓名] — [职位]
| 字段 | 详情 |
|-------|--------|
| **LinkedIn** | [URL] |
| **背景** | [前公司、教育经历] |
| **任职时间** | [在公司的时间] |
| **邮箱** | [如果连接了数据增强] |
**谈话切入点:**
- [基于背景的个人切入点]
- [基于角色的专业切入点]
[为相关联系人重复此部分]
---
## 技术栈 [如果连接了数据增强]
| 类别 | 工具 |
|----------|-------|
| **云服务** | [AWS, GCP, Azure 等] |
| **数据** | [Snowflake, Databricks 等] |
| **CRM** | [例如 Salesforce, HubSpot] |
| **其他** | [相关工具] |
**整合机会:** [您的产品如何与其技术栈结合]
---
## 过往关系 [如果连接了 CRM]
| 字段 | 详情 |
|-------|--------|
| **状态** | [新线索 / 历史潜在客户 / 客户 / 流失客户] |
| **最后联系** | [日期和类型] |
| **历史商机** | [赢单/输单及原因] |
| **已知联系人** | [CRM 中已有的姓名] |
**历史记录:** [过往关系摘要]
---
## 资质信号
### 积极信号
- ✅ [信号及证据]
- ✅ [信号及证据]
### 潜在顾虑
- ⚠️ [顾虑及需关注点]
### 未知信息(需在发现阶段询问)
- ❓ [理解上的空白]
---
## 推荐方案
**最佳切入点:** [人物及原因]
**开场钩子:** [基于调研的引导话题]
**发现阶段问题:**
1. [关于其现状的问题]
2. [关于痛点的问题]
3. [关于决策流程的问题]
---
## 信息来源
- [来源 1](URL)
- [来源 2](URL)
确定调研对象:
- "调研 Stripe" → 公司调研
- "查找 Acme 的 John Smith" → 个人 + 公司
- "Notion 的 CTO 是谁" → 基于角色的搜索
- "获取 acme.com 的情报" → 基于域名的查找
执行以下搜索:
1. "[公司名称]" → 主页、关于页面
2. "[公司名称] 新闻" → 近期公告
3. "[公司名称] 融资" → 投资历史
4. "[公司名称] 招聘" → 招聘信号
5. "[姓名] [公司] LinkedIn" → 个人资料信息
6. "[公司名称] 产品" → 销售内容
7. "[公司名称] 客户" → 服务对象
提取内容:
如果数据增强工具可用:
1. 增强公司信息 → 企业统计数据、融资情况、技术栈
2. 搜索人员 → 组织架构图、联系人列表
3. 增强个人信息 → 邮箱、电话、背景
4. 获取信号 → 意向数据、招聘速度
数据增强新增:
如果 CRM 可用:
1. 按域名搜索客户
2. 获取相关联系人
3. 获取商机历史
4. 获取活动时间线
CRM 新增:
1. 合并所有来源
2. 优先使用数据增强数据而非网络数据(更准确)
3. 添加 CRM 背景(如果存在)
4. 识别资质信号
5. 生成谈话切入点
6. 推荐方案
关注点:业务概览、新闻、招聘、领导层
关注点:背景、角色、LinkedIn 动态、谈话切入点
关注点:产品对比、市场定位、赢单/输单模式
关注点:与会者背景、近期新闻、关系历史
每周安装量
168
代码仓库
GitHub 星标数
8.8K
首次出现
Jan 31, 2026
安全审计
安装于
opencode147
codex143
gemini-cli138
claude-code135
github-copilot128
cursor121
Get a complete picture of any company or person before outreach. This skill always works with web search, and gets significantly better with enrichment and CRM data.
┌─────────────────────────────────────────────────────────────────┐
│ ACCOUNT RESEARCH │
├─────────────────────────────────────────────────────────────────┤
│ ALWAYS (works standalone via web search) │
│ ✓ Company overview: what they do, size, industry │
│ ✓ Recent news: funding, leadership changes, announcements │
│ ✓ Hiring signals: open roles, growth indicators │
│ ✓ Key people: leadership team from LinkedIn │
│ ✓ Product/service: what they sell, who they serve │
├─────────────────────────────────────────────────────────────────┤
│ SUPERCHARGED (when you connect your tools) │
│ + Enrichment: verified emails, phone, tech stack, org chart │
│ + CRM: prior relationship, past opportunities, contacts │
└─────────────────────────────────────────────────────────────────┘
Just tell me who to research:
I'll run web searches immediately. If you have enrichment or CRM connected, I'll pull that data too.
Connect your tools to supercharge this skill:
| Connector | What It Adds |
|---|---|
| Enrichment | Verified emails, phone numbers, tech stack, org chart, funding details |
| CRM | Prior relationship history, past opportunities, existing contacts, notes |
No connectors? No problem. Web search provides solid research for any company or person.
# Research: [Company or Person Name]
**Generated:** [Date]
**Sources:** Web Search [+ Enrichment] [+ CRM]
---
## Quick Take
[2-3 sentences: Who they are, why they might need you, best angle for outreach]
---
## Company Profile
| Field | Value |
|-------|-------|
| **Company** | [Name] |
| **Website** | [URL] |
| **Industry** | [Industry] |
| **Size** | [Employee count] |
| **Headquarters** | [Location] |
| **Founded** | [Year] |
| **Funding** | [Stage + amount if known] |
| **Revenue** | [Estimate if available] |
### What They Do
[1-2 sentence description of their business, product, and customers]
### Recent News
- **[Headline]** — [Date] — [Why it matters for your outreach]
- **[Headline]** — [Date] — [Why it matters]
### Hiring Signals
- [X] open roles in [Department]
- Notable: [Relevant roles like Engineering, Sales, AI/ML]
- Growth indicator: [Hiring velocity interpretation]
---
## Key People
### [Name] — [Title]
| Field | Detail |
|-------|--------|
| **LinkedIn** | [URL] |
| **Background** | [Prior companies, education] |
| **Tenure** | [Time at company] |
| **Email** | [If enrichment connected] |
**Talking Points:**
- [Personal hook based on background]
- [Professional hook based on role]
[Repeat for relevant contacts]
---
## Tech Stack [If Enrichment Connected]
| Category | Tools |
|----------|-------|
| **Cloud** | [AWS, GCP, Azure, etc.] |
| **Data** | [Snowflake, Databricks, etc.] |
| **CRM** | [e.g. Salesforce, HubSpot] |
| **Other** | [Relevant tools] |
**Integration Opportunity:** [How your product fits with their stack]
---
## Prior Relationship [If CRM Connected]
| Field | Detail |
|-------|--------|
| **Status** | [New / Prior prospect / Customer / Churned] |
| **Last Contact** | [Date and type] |
| **Previous Opps** | [Won/Lost and why] |
| **Known Contacts** | [Names already in CRM] |
**History:** [Summary of past relationship]
---
## Qualification Signals
### Positive Signals
- ✅ [Signal and evidence]
- ✅ [Signal and evidence]
### Potential Concerns
- ⚠️ [Concern and what to watch for]
### Unknown (Ask in Discovery)
- ❓ [Gap in understanding]
---
## Recommended Approach
**Best Entry Point:** [Person and why]
**Opening Hook:** [What to lead with based on research]
**Discovery Questions:**
1. [Question about their situation]
2. [Question about pain points]
3. [Question about decision process]
---
## Sources
- [Source 1](URL)
- [Source 2](URL)
Identify what to research:
- "Research Stripe" → Company research
- "Look up John Smith at Acme" → Person + company
- "Who is the CTO at Notion" → Role-based search
- "Intel on acme.com" → Domain-based lookup
Run these searches:
1. "[Company name]" → Homepage, about page
2. "[Company name] news" → Recent announcements
3. "[Company name] funding" → Investment history
4. "[Company name] careers" → Hiring signals
5. "[Person name] [Company] LinkedIn" → Profile info
6. "[Company name] product" → What they sell
7. "[Company name] customers" → Who they serve
Extract:
If enrichment tools available:
1. Enrich company → Firmographics, funding, tech stack
2. Search people → Org chart, contact list
3. Enrich person → Email, phone, background
4. Get signals → Intent data, hiring velocity
Enrichment adds:
If CRM available:
1. Search for account by domain
2. Get related contacts
3. Get opportunity history
4. Get activity timeline
CRM adds:
1. Combine all sources
2. Prioritize enrichment data over web (more accurate)
3. Add CRM context if exists
4. Identify qualification signals
5. Generate talking points
6. Recommend approach
Focus on: Business overview, news, hiring, leadership
Focus on: Background, role, LinkedIn activity, talking points
Focus on: Product comparison, positioning, win/loss patterns
Focus on: Attendee backgrounds, recent news, relationship history
Weekly Installs
168
Repository
GitHub Stars
8.8K
First Seen
Jan 31, 2026
Security Audits
Gen Agent Trust HubPassSocketPassSnykWarn
Installed on
opencode147
codex143
gemini-cli138
claude-code135
github-copilot128
cursor121
Azure RBAC 权限管理工具:查找最小角色、创建自定义角色与自动化分配
101,200 周安装