Lead generation
Collection of Claude Code Agent Skills for founders, indie hackers, and growth engineers
npx -y skills add PHY041/claude-agent-skills --skill lead-generationAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
- 18 stars18 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
Lead Generation — Find high-intent buyers in live Twitter, Instagram, and Reddit conversations. Auto-researches your product, generates targeted search queries, and discovers people actively looking for solutions you offer. Social selling and prospecting powered by 1.5B+ indexed posts via Xpoz MCP.
SKILL.md
4.6 KB, as published. Nobody here has run it
Lead Generation
Find high-intent buyers from live social conversations.
Discovers leads expressing problems your product solves, complaining about competitors, or actively seeking solutions across Twitter, Instagram, and Reddit.
Setup
Run xpoz-setup skill to authenticate. Verify: mcporter call xpoz.checkAccessKeyStatus
3-Phase Process
Phase 1: Product Research (One-Time)
Ask for product reference (website/GitHub/description). Use web_fetch/web_search to research. Build profile:
- Product description
- Target audience / ICP
- Pain points addressed
- Competitors
- Keywords
Validate with user before proceeding.
Generate 12-18 search queries across:
- Pain point queries — people expressing problems your product solves
- Competitor frustration — complaints about alternatives
- Tool/solution seeking — "recommend a tool for..."
- Industry discussion — target audience conversations
Save to data/lead-generation/product-profile.json and data/lead-generation/search-queries.json.
Phase 2: Lead Discovery (Repeatable)
# Twitter posts (highest intent signal)
mcporter call xpoz.getTwitterPostsByKeywords query="QUERY" startDate="DATE"
# Poll for results (every 5s until completed)
mcporter call xpoz.checkOperationStatus operationId="op_..."
# Find relevant people
mcporter call xpoz.getTwitterUsersByKeywords query="..."
# Reddit posts (good for tool comparison threads)
mcporter call xpoz.getRedditPostsByKeywords query="QUERY" limit=10
Phase 3: Scoring & Output
Score (1-10):
| Signal | Points |
|---|---|
| Explicitly asking for tool/solution | +3 |
| Complaining about named competitor | +2 |
| Project blocked by pain point | +2 |
| Active in target community | +1 |
| High engagement (>10 likes / 5 comments) | +1 |
| Recent (<48h) | +1 |
| Profile matches ICP | +1 |
| Is selling a competing product | -3 |
| Is a KOL/content creator (not a buyer) | -2 |
Tiers: 8-10 = 🔴 Hot (outreach now), 6-7 = 🟠 Warm (monitor), 5 = Watchlist, <5 = Skip
Deduplicate via data/lead-generation/sent-leads.json (key: {platform}:{author}:{post_id}).
Output format for each lead:
🔴 HOT LEAD (Score: 8/10)
@username | Job Title | Platform
"Quote from their post..."
URL: https://...
Posted: X days ago | Y likes, Z replies
Why: [Signal breakdown]
Outreach draft:
"Had the exact same problem — we ended up building [solution].
Happy to share what worked. (Disclosure: I work on [Product])"
Query Limitations (Xpoz)
Xpoz uses split-word matching, NOT phrase matching.
- "brand voice" → matches "brand" OR "voice" → noisy results
- FIX: Use domain-specific compound terms with unique identifiers
- Competitor queries work best because competitor names are unique
Tips
- Save product profile once, reuse daily
- Quality > quantity — filter aggressively
- Always disclose affiliations in outreach drafts
- Drafts only — user reviews before sending
- Daily budget: ~6 queries/day on free tier (~5,000 credits total)