/lead-generation
Finds and qualifies B2B leads from X/Twitter conversations using keyword search, profile analysis, and intent scoring. Combines MCP tools for automated prospecting pipelines. Use when prospecting, finding potential customers, or mining social conversations for leads.
$ npx -y skills add nirholas/XActions --skill lead-generation --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/lead-generation
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The summary Claude sees to decide when to auto-load this skill.
Finds and qualifies B2B leads from X/Twitter conversations using keyword search, profile analysis, and intent scoring. Combines MCP tools for automated prospecting pipelines. Use when prospecting, finding potential customers, or mining social conversations for leads.
SKILL.md
lead-generation.SKILL.mdname: lead-generation
description: Finds and qualifies B2B leads from X/Twitter conversations using keyword search, profile analysis, and intent scoring. Combines MCP tools for automated prospecting pipelines. Use when prospecting, finding potential customers, or mining social conversations for leads.
license: Apache-2.0
metadata:
author: nichxbt
version: "4.0"
Lead Generation
MCP-powered workflow for finding and qualifying B2B leads from X/Twitter conversations and profiles.
MCP Tools Used
| Tool | Purpose | |------|---------| | `x_search_tweets` | Find conversations by keyword/intent | | `x_get_profile` | Qualify leads with profile data | | `x_get_tweets` | Assess activity level and interests | | `x_get_followers` | Check audience size and quality | | `x_get_following` | Identify competitor usage / peer network |
Workflow
1. **Define search queries** -- Build 3-5 keyword queries combining pain points, competitor names, or buying signals (e.g., "looking for {tool}", "anyone recommend {category}", "switching from {competitor}"). 2. **Search conversations** -- Call `x_search_tweets` for each query with `limit: 30`. Collect unique usernames. 3. **Qualify profiles** -- Call `x_get_profile` for each. Filter by: has bio, followers > 100, account age > 6 months. 4. **Score intent** -- Assign 1-5 score:
- 5: Explicit buying intent ("need a tool for...", "budget approved")
- 4: Comparing solutions ("X vs Y", "switching from")
- 3: Pain point discussion ("struggling with...")
- 2: Topic interest (engages with industry content)
- 1: Tangential mention
5. **Gather context** -- For top leads (4-5), call `x_get_tweets` with `limit: 20`. 6. **Check network** -- Call `x_get_following` for high-value leads to see competitor follows. 7. **Export lead list** -- Format as structured output.
Browser Script Integration
Enhance MCP workflows with browser scripts:
| Goal | Script | |------|--------| | Monitor keywords in real-time | `src/keywordMonitor.js` | | Analyze potential lead's audience | `src/audienceDemographics.js` | | Check overlap with your audience | `src/audienceOverlap.js` | | Engage with leads' content | `src/engagementBooster.js` | | Auto-follow qualified leads | `src/automation/keywordFollow.js` |
Output Template
## Lead List: {search_topic}
Generated: {date} | Total qualified: {count}
| Username | Score | Followers | Signal | Tweet URL |
|----------|-------|-----------|--------|-----------|
| @{user} | {1-5} | {count} | {type} | {url} |
### High-Priority Leads (Score 4-5)
**@{username}** -- Score: {n}/5
- Signal: "{tweet excerpt}"
- Bio: {bio}
- Suggested approach: {personalized outreach note}Tips
- Run searches at different times to catch varied audiences
- Refresh weekly -- buying signals are time-sensitive
- Cross-reference with `x_get_followers` to find warm intros
- Use `src/keywordMonitor.js` for ongoing keyword monitoring
Read more
name: lead-generation description: Finds and qualifies B2B leads from X/Twitter conversations using keyword search, profile analysis, and intent scoring. Combines MCP tools for automated prospecting pipelines. Use when prospecting, finding potential customers, or mining social conversations for leads. license: Apache-2.0 metadata: author: nichxbt version: "4.0"
Lead Generation
MCP-powered workflow for finding and qualifying B2B leads from X/Twitter conversations and profiles.
MCP Tools Used
| Tool | Purpose | |------|---------| | `x_search_tweets` | Find conversations by keyword/intent | | `x_get_profile` | Qualify leads with profile data | | `x_get_tweets` | Assess activity level and interests | | `x_get_followers` | Check audience size and quality | | `x_get_following` | Identify competitor usage / peer network |
Workflow
1. **Define search queries** -- Build 3-5 keyword queries combining pain points, competitor names, or buying signals (e.g., "looking for {tool}", "anyone recommend {category}", "switching from {competitor}"). 2. **Search conversations** -- Call `x_search_tweets` for each query with `limit: 30`. Collect unique usernames. 3. **Qualify profiles** -- Call `x_get_profile` for each. Filter by: has bio, followers > 100, account age > 6 months. 4. **Score intent** -- Assign 1-5 score:
- 5: Explicit buying intent ("need a tool for...", "budget approved")
- 4: Comparing solutions ("X vs Y", "switching from")
- 3: Pain point discussion ("struggling with...")
- 2: Topic interest (engages with industry content)
- 1: Tangential mention
5. **Gather context** -- For top leads (4-5), call `x_get_tweets` with `limit: 20`. 6. **Check network** -- Call `x_get_following` for high-value leads to see competitor follows. 7. **Export lead list** -- Format as structured output.
Browser Script Integration
Enhance MCP workflows with browser scripts:
| Goal | Script | |------|--------| | Monitor keywords in real-time | `src/keywordMonitor.js` | | Analyze potential lead's audience | `src/audienceDemographics.js` | | Check overlap with your audience | `src/audienceOverlap.js` | | Engage with leads' content | `src/engagementBooster.js` | | Auto-follow qualified leads | `src/automation/keywordFollow.js` |
Output Template
## Lead List: {search_topic}
Generated: {date} | Total qualified: {count}
| Username | Score | Followers | Signal | Tweet URL |
|----------|-------|-----------|--------|-----------|
| @{user} | {1-5} | {count} | {type} | {url} |
### High-Priority Leads (Score 4-5)
**@{username}** -- Score: {n}/5
- Signal: "{tweet excerpt}"
- Bio: {bio}
- Suggested approach: {personalized outreach note}Tips
- Run searches at different times to catch varied audiences
- Refresh weekly -- buying signals are time-sensitive
- Cross-reference with `x_get_followers` to find warm intros
- Use `src/keywordMonitor.js` for ongoing keyword monitoring
⚡ The Complete X/Twitter Automation Toolkit — Scrapers, MCP server for AI agents (Claude/GPT), CLI, browser scripts. No API fees. Open source. Unfollow people who don't follow back. Monitor real-time analytics. Auto follow, like, comment, scrape, without API. Follow Bot. Like bot. Grow your account automatically.
Repo: nirholas/XActions
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