enrich-lead
Instant lead enrichment. Drop a name, company, LinkedIn URL, or email and get the full contact card with email, phone, title, company intel, and next actions.
DeepseekModel
官方收录技能
质量 优秀 · 90
v1.0.0
获取
https://deepseekmodel.com/api/download.php?id=anthropics-knowledge-work-plugins-partner-built-apollo-skills-enrich-lead-skill-md&format=skill
下载 .skill
标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
name enrich-lead description Instant lead enrichment. Drop a name, company, LinkedIn URL, or email and get the full contact card with email, phone, title, company intel, and next actions. user-invocable true argument-hint [name, company, LinkedIn URL, or email] Enrich Lead Turn any identifier into a full contact dossier. The user provides identifying info via "$ARGUMENTS". Examples /apollo:enrich-lead Tim Zheng at Apollo /apollo:enrich-lead https://www.linkedin.com/in/timzheng /apollo:enrich-lead sarah@stripe.com /apollo:enrich-lead Jane Smith, VP Engineering, Notion /apollo:enrich-lead CEO of Figma Step 1 — Parse Input From "$ARGUMENTS", extract every identifier available: First name, last name Company name or domain LinkedIn URL Email address Job title (use as a matching hint) If the input is ambiguous (e.g. just "CEO of Figma"), first use mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search with relevant title and domain filters to identify the person, then proceed to enrichment. Step 2 — Enrich the Person Credit warning : Tell the user enrichment consumes 1 Apollo credit before calling. Use mcp__claude_ai_Apollo_MCP__apollo_people_match with all available identifiers: first_name , last_name if name is known domain or organization_name if company is known linkedin_url if LinkedIn is provided email if email is provided Set reveal_personal_emails to true If the match fails, try mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search with looser filters and present the top 3 candidates. Ask the user to pick one, then re-enrich. Step 3 — Enrich Their Company Use mcp__claude_ai_Apollo_MCP__apollo_organizations_enrich with the person's company domain to pull firmographic context. Step 4 — Present the Contact Card Format the output exactly like this: [Full Name] | [Title] [Company Name] · [Industry] · [Employee Count] employees Field Detail Email (work) ... Email (personal) ... (if revealed) Phone (direct) ... Phone (mobile) ... Phone (corporate) ... Location City, State, Country LinkedIn URL Company Domain ... Company Revenue Range Company Funding Total raised Company HQ Location Step 5 — Offer Next Actions Ask the user which action to take: Save to Apollo — Create this person as a contact via mcp__claude_ai_Apollo_MCP__apollo_contacts_create with run_dedupe: true Add to a sequence — Ask which sequence, then run the sequence-load flow Find colleagues — Search for more people at the same company using mcp__claude_ai_Apollo_MCP__apollo_mixed_people_api_search with q_organization_domains_list set to this company Find similar people — Search for people with the same title/seniority at other companies
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该技能未提供触发词。
下载的 .skill 包内含以下字段。
| 字段 | 说明 |
|---|---|
| format | 格式标识(skill/v1) |
| skill_id | 技能唯一 ID |
| name | 技能名称 |
| version | 版本号 |
| description | 技能描述 |
| category | 所属分类(数组) |
| trigger_words | 触发词列表 |
| tags | 标签列表 |
| source | 来源标识 |
| source_url | 来源链接(本页地址) |
| exported_at | 导出时间(每次下载生成) |
| system_prompt | 系统提示词正文 |
| model_config | 模型参数:provider / model / temperature / max_tokens / top_p |
| examples | 示例 |
| install_guide | 各平台导入说明(Coze / Dify / Claude / 自定义框架) |