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nirholasnirholas/XActions/skills/lead-generation/SKILL.md

lead-generation

Skill648 starsChanged 9 months agoApache-2.0View on GitHub

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.

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The file

We split this skill into the rules it gives an agent

2 rules. 0 are common, 1 is distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 5 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Run searches at different times to catch varied audiences

    line 70
  2. Very specific:

    Use src/keywordMonitor.js for ongoing keyword monitoring

    line 73

“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Lead Generation

MCP-powered workflow for finding and qualifying B2B leads from X/Twitter conversations and profiles.

MCP Tools Used

ToolPurpose
x_search_tweetsFind conversations by keyword/intent
x_get_profileQualify leads with profile data
x_get_tweetsAssess activity level and interests
x_get_followersCheck audience size and quality
x_get_followingIdentify 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:

GoalScript
Monitor keywords in real-timesrc/keywordMonitor.js
Analyze potential lead's audiencesrc/audienceDemographics.js
Check overlap with your audiencesrc/audienceOverlap.js
Engage with leads' contentsrc/engagementBooster.js
Auto-follow qualified leadssrc/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

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