Lead Qualification Skill

Lead Qualification Skill

【免费下载链接】goose-skillsLibrary of Growth & GTM skills + data APIs for Claude Code, Codex, Cursor to run ads, social, content, lead gen, seo and data scraping项目地址: https://gitcode.com/gh_mirrors/go/goose-skills

This skill analyzes lead data and qualifies prospects based on predefined criteria.

Usage

/gooseworks Use the lead-qualification skill to analyze leads from the CSV file.

Parameters

• criteria: JSON object defining qualification criteria
• lead_source: Path to CSV file or API endpoint with lead data
• scoring_model: Optional scoring model configuration

Output

A qualified leads report with scores and recommendations.

### 第三步：编写技能实现脚本 创建`scripts/qualify_leads.py`文件，实现核心功能： ```python import csv import json import argparse def load_lead_data(file_path): """Load lead data from CSV file""" leads = [] with open(file_path, 'r') as csvfile: reader = csv.DictReader(csvfile) for row in reader: leads.append(row) return leads def apply_scoring_model(lead, criteria): """Apply scoring model to a single lead""" score = 0 for key, weight in criteria.items(): if key in lead and lead[key].lower() in ['yes', 'true', '1']: score += weight return score def qualify_leads(lead_data, criteria): """Qualify leads based on criteria""" qualified = [] for lead in lead_data: score = apply_scoring_model(lead, criteria) qualified.append({ 'lead': lead, 'score': score, 'qualified': score >= criteria.get('threshold', 70) }) return qualified def main(): parser = argparse.ArgumentParser(description='Lead Qualification Tool') parser.add_argument('--leads', required=True, help='Path to CSV file with lead data') parser.add_argument('--criteria', required=True, help='JSON file with qualification criteria') args = parser.parse_args() # Load data leads = load_lead_data(args.leads) with open(args.criteria, 'r') as f: criteria = json.load(f) # Process leads results = qualify_leads(leads, criteria) # Output results print(json.dumps(results, indent=2)) if __name__ == "__main__": main()

第四步：测试与验证技能

创建测试用例和验证脚本：

mkdir tests touch tests/test_leads.csv touch tests/test_criteria.json

在tests/test_criteria.json中定义测试标准：

{ "company_size": 20, "industry_match": 30, "budget_range": 25, "decision_authority": 25, "threshold": 70 }

运行验证脚本检查技能是否符合规范：

node ../../../../../scripts/validate-skills.js

📝 技能注册与发布

本地测试与调试

在发布技能之前，先在本地进行测试：

npx goose-skills install ./skills/lead-generation/capabilities/lead-qualification npx goose-skills run lead-qualification --leads tests/test_leads.csv --criteria tests/test_criteria.json

更新技能索引

将新技能添加到技能索引：

node scripts/build-index.js

这会更新项目根目录下的skills-index.json文件，包含你的新技能信息。

提交与发布流程

按照项目贡献指南提交你的技能：

1. 创建技能分支
2. 提交代码并推送到仓库
3. 创建Pull Request
4. 通过代码审查
5. 合并到主分支

💡 高级技巧：技能组合与自动化工作流

组合现有技能创建复合技能

Goose Skills支持通过组合现有技能创建更复杂的复合技能。例如，创建一个"lead-generation-pipeline"复合技能，组合以下能力：

1. apollo-lead-finder：寻找潜在客户
2. lead-enrichment：丰富客户数据
3. lead-qualification：筛选高质量客户
4. cold-email-outreach：发送个性化邮件

创建skills/lead-generation/composites/lead-generation-pipeline/skill.meta.json：

{ "slug": "lead-generation-pipeline", "category": "composites", "description": "End-to-end lead generation pipeline from prospect finding to outreach.", "tags": ["lead-generation", "sales", "outreach"], "installation": { "base_command": "npx goose-skills install lead-generation-pipeline", "supports": ["claude", "cursor", "codex"] }, "requires_skills": [ "apollo-lead-finder", "lead-enrichment", "lead-qualification", "cold-email-outreach" ] }

【免费下载链接】goose-skillsLibrary of Growth & GTM skills + data APIs for Claude Code, Codex, Cursor to run ads, social, content, lead gen, seo and data scraping项目地址: https://gitcode.com/gh_mirrors/go/goose-skills