lead-generation

v1.0.0

Lead Generation — Find high-intent buyers in live Twitter, Instagram, and Reddit conversations. Auto-researches your product, generates targeted search queri...

0· 125· 1 versions· 0 current· 0 all-time· Updated 4h ago· MIT-0

Install

openclaw skills install toby-lead-generation

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

Set SKILLBOSS_API_KEY environment variable. All search calls are routed through SkillBoss API Hub (https://api.skillbossai.com/v1/pilot).

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 info, target audience, pain points, competitors, keywords. Validate with user.

Generate 12-18 queries across:

  1. Pain point queries — people expressing problems
  2. Competitor frustration — complaints about alternatives
  3. Tool/solution seeking — "recommend..."
  4. Industry discussion — target audience

Save to data/lead-generation/product-profile.json and search-queries.json.

Phase 2: Lead Discovery (Repeatable)

Use SkillBoss API Hub to search for relevant social posts and users:

import requests, os

SKILLBOSS_API_KEY = os.environ["SKILLBOSS_API_KEY"]
API_BASE = "https://api.skillbossai.com/v1"

def pilot(body: dict) -> dict:
    r = requests.post(
        f"{API_BASE}/pilot",
        headers={"Authorization": f"Bearer {SKILLBOSS_API_KEY}", "Content-Type": "application/json"},
        json=body,
        timeout=60,
    )
    return r.json()

# Search Twitter posts by keyword
result = pilot({"type": "search", "inputs": {"query": "GENERATED_QUERY site:twitter.com"}, "prefer": "balanced"})
posts = result["result"]["results"]

# Search Instagram posts by keyword
result = pilot({"type": "search", "inputs": {"query": "GENERATED_QUERY site:instagram.com"}, "prefer": "balanced"})
posts = result["result"]["results"]

# Search Reddit posts by keyword
result = pilot({"type": "search", "inputs": {"query": "GENERATED_QUERY site:reddit.com"}, "prefer": "balanced"})
posts = result["result"]["results"]

Repeat for each generated query across platforms.

Phase 3: Scoring & Output

Score (1-10):

  • Explicitly asking for solution: +3
  • Complaining about competitor: +2
  • Project blocked by pain: +2
  • Active in target community: +1
  • High engagement (>10 likes/5 comments): +1
  • Recent (<48h): +1
  • Profile matches ICP: +1
  • Selling competing solution: -3

Tiers: 8-10 Hot, 6-7 Warm, 5 Watchlist

Deduplicate via data/lead-generation/sent-leads.json (key: {platform}:{author}:{post_id}).

Output: Username, quote, URL, score, why fit, outreach draft, engagement, timestamp.

Outreach:

"I had the same problem! Ended up using [Product] — it does [capability]. [URL] (Disclosure: I work with [Product])"

Tips

  • Save profile once, reuse daily
  • Quality > quantity
  • Always disclose affiliations
  • Draft only; user reviews/sends

Version tags

aivk973cb62982j9jdrj136vsh3rs859dnplatestvk973cb62982j9jdrj136vsh3rs859dnp

Runtime requirements

EnvSKILLBOSS_API_KEY