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Account Research

作者 Patrick Roland · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install account-research
功能描述
Research a company or person and get actionable sales intel. Works standalone with web search, supercharged when you connect enrichment tools or your CRM. Tr...
使用说明 (SKILL.md)

Account Research

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.

How It Works

┌─────────────────────────────────────────────────────────────────┐
│                     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        │
└─────────────────────────────────────────────────────────────────┘

Getting Started

Just tell me who to research:

  • "Research Stripe"
  • "Look up the CTO at Notion"
  • "Intel on acme.com"
  • "Who is Sarah Chen at TechCorp?"
  • "Tell me about [company] before my call"

I'll run web searches immediately. If you have enrichment or CRM connected, I'll pull that data too.


Connectors (Optional)

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.


Output Format

# 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)

Execution Flow

Step 1: Parse Request

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

Step 2: Web Search (Always)

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:

  • Company description and positioning
  • Recent news (last 90 days)
  • Leadership team
  • Open job postings
  • Technology mentions
  • Customer base

Step 3: Enrichment (If Connected)

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:

  • Verified contact info
  • Complete org chart
  • Precise employee count
  • Detailed tech stack
  • Funding history with investors

Step 4: CRM Check (If Connected)

If CRM available:
1. Search for account by domain
2. Get related contacts
3. Get opportunity history
4. Get activity timeline

CRM adds:

  • Prior relationship context
  • What happened before (won/lost deals)
  • Who we've talked to
  • Notes and history

Step 5: Synthesize

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

Research Variations

Company Research

Focus on: Business overview, news, hiring, leadership

Person Research

Focus on: Background, role, LinkedIn activity, talking points

Competitor Research

Focus on: Product comparison, positioning, win/loss patterns

Pre-Meeting Research

Focus on: Attendee backgrounds, recent news, relationship history


Tips for Better Research

  1. Include the domain — "research acme.com" is more precise
  2. Specify the person — "look up Jane Smith, VP Sales at Acme"
  3. State your goal — "research Stripe before my demo call"
  4. Ask for specifics — "what's their tech stack?" after initial research

Related Skills

  • call-prep — Full meeting prep with this research plus context
  • draft-outreach — Write personalized message based on research
  • prospecting — Qualify and prioritize research targets
安全使用建议
Install only if you are comfortable with the skill querying connected enrichment or CRM systems for account research. Prefer configuring least-privilege connectors, requiring explicit confirmation before CRM/enrichment lookups, and limiting display of personal contact details and internal notes by default.
能力评估
Purpose & Capability
Company/account research is coherent with web search, enrichment, and CRM lookups, but the described connector data can include sensitive contact or relationship information.
Instruction Scope
The invocation examples are broad, including 'tell me about [company]' and a pre-call company briefing phrasing, which can overlap with ordinary conversation rather than explicit connector-backed research intent.
Install Mechanism
No concrete install-time code execution, package script, or privileged installer behavior was provided in the reviewed evidence.
Credentials
Use of connected enrichment or CRM systems is proportionate for account research, but the available evidence does not show clear minimization or consent before surfacing personal contact details or internal CRM context.
Persistence & Privilege
No persistence mechanism, background worker, privilege escalation, or credential harvesting behavior was evidenced; concern is centered on connector-backed sensitive data access and disclosure.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install account-research
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /account-research 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of the account-research skill. - Instantly researches any company or person using web search, with actionable sales insights. - Enhanced with optional connectors: add enrichment (email, phone, tech stack, org chart) or CRM data (history, contacts, past opportunities). - Flexible triggers: start research easily with natural phrases like “research [company]” or “intel on [person]”. - Output includes company overview, recent news, hiring signals, leadership bios, tech stack, CRM history, and outreach recommendations. - Works standalone—connectors are not required for core research.
元数据
Slug account-research
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Account Research 是什么?

Research a company or person and get actionable sales intel. Works standalone with web search, supercharged when you connect enrichment tools or your CRM. Tr... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 59 次。

如何安装 Account Research?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install account-research」即可一键安装,无需额外配置。

Account Research 是免费的吗?

是的,Account Research 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Account Research 支持哪些平台?

Account Research 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Account Research?

由 Patrick Roland(@rolandpg)开发并维护,当前版本 v1.0.0。

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