lead-generation
npx machina-cli add skill PHY041/claude-agent-skills/lead-generation --openclawLead 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)
Source
git clone https://github.com/PHY041/claude-agent-skills/blob/main/skills/lead-generation/SKILL.mdView on GitHub Overview
Lead Generation helps you locate high-intent buyers in live conversations across Twitter, Instagram, and Reddit. It auto-researches your product to build a profile, generates targeted search queries, and surfaces people actively seeking solutions you offer. Powered by Xpoz MCP with 1.5B+ indexed posts.
How This Skill Works
Phase 1 conducts product research using web_fetch/web_search to build a product-profile (description, ICP, pain points, competitors, keywords). Phase 2 discovers leads by querying social posts and users with generated keywords (via mcporter calls to xpoz.getTwitterPostsByKeywords, xpoz.getTwitterUsersByKeywords, and xpoz.getRedditPostsByKeywords). Phase 3 scores each lead against defined signals and outputs outreach-ready drafts, deduplicated in data/lead-generation/sent-leads.json.
When to Use It
- When launching a new product and you need to identify ICP-ready conversations and high-potential prospects
- When you want to optimize outbound outreach with live social signals and buyer intent
- When researching competitor pain points and tool recommendations to surface dissatisfied users
- When you need structured, evidence-backed outreach drafts aligned to each lead
- When you want a repeatable, data-driven flow to surface and score leads from Twitter, Instagram, and Reddit
Quick Start
- Step 1: Run xpoz-setup to authenticate; verify access with mcporter call xpoz.checkAccessKeyStatus
- Step 2: Provide product_description or product_url; Phase 1 will build the product-profile and generate search-queries.json
- Step 3: Run Phase 2 (Twitter/Reddit discovery) and Phase 3 (score and export leads to data/lead-generation/sent-leads.json)
Best Practices
- Run Phase 1 (Product Research) first and validate the profile with the user before proceeding
- Generate 12-18 search queries across pain points, competitor frustration, tool-seeking, and industry discussions
- Surface posts and users with Phase 2 commands, then deduplicate with data/lead-generation/sent-leads.json
- Apply the Phase 3 scoring criteria to prioritize outreach and identify HOT vs. Warm vs. Watchlist leads
- Use the provided outreach draft format and personalize messages for higher reply rates
Example Use Cases
- A project-management SaaS identifies IT pros expressing frustration with manual reporting and surfaces high-scoring leads for outreach
- A marketing automation vendor finds Reddit threads where teams complain about existing tools, yielding warm opportunities
- Users asking for tool recommendations on Twitter trigger queries that surface potential buyers with high intent
- Industry discussions about automation reveal prospects actively exploring solutions your product solves
- Open discussions by influencers or KOLs are filtered for relevance and converted into outreach-ready leads
