/install jx-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:
- Pain point queries — people expressing problems
- Competitor frustration — complaints about alternatives
- Tool/solution seeking — "recommend..."
- 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 (\x3C48h): +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
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install jx-lead-generation - 安装完成后,直接呼叫该 Skill 的名称或使用
/jx-lead-generation触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
lead-generation 是什么?
Lead Generation — Find high-intent buyers in live Twitter, Instagram, and Reddit conversations. Auto-researches your product, generates targeted search queri... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 136 次。
如何安装 lead-generation?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install jx-lead-generation」即可一键安装,无需额外配置。
lead-generation 是免费的吗?
是的,lead-generation 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
lead-generation 支持哪些平台?
lead-generation 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 lead-generation?
由 KirkRaman(@kirkraman)开发并维护,当前版本 v1.0.0。