Token导航 LogoToken导航TokenDH.com
研究检索需要联网clawhub未标认证来源可访问clear审计通过

ironclaw-lead-enrichment铁爪铅浓缩

Agent Skill

ironclaw-lead-enrichment 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

19,560

周安装

799

GitHub Stars

公开资料未说明

下载量

6,328
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ironclaw-lead-enrichment(铁爪铅浓缩)
来源仓库:https://github.com/aspenas/ironclaw-lead-enrichment
安装命令:
openclaw skills install ironclaw-lead-enrichment
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install ironclaw-lead-enrichment

简介

用于丰富联系人和潜在客户的基础信息。

  • 整合 LinkedIn 资料、邮箱和公司教育数据。
  • 提升 CRM 系统中客户画像完整性。
  • 需用户提供待处理联系人列表。ironclaw-lead-enrichment 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 涉及隐私数据时应遵守 GDPR 等法规。

SKILL.md

name
lead-enrichment
description
Enrich contact and lead records with LinkedIn profiles, email addresses, company data, and education info. Use when asked to "enrich contacts", "fill in missing data", "find emails for leads", "complete lead profiles", "look up company info", or any bulk data completion task for CRM records.
metadata
{ "openclaw": { "emoji": "✨" } }

Lead Enrichment — Multi-Source Data Completion

Enrich CRM contact records by filling missing fields from multiple sources. Works with DuckDB workspace entries or standalone JSON data.

Sources (Priority Order)

  1. LinkedIn (via linkedin-scraper skill) — name, title, company, education, connections
  2. Web Search (via web_search tool) — email patterns, company info, social profiles
  3. Company Website (via web_fetch) — team pages, about pages, contact info
  4. Email Pattern Discovery — derive email from name + company domain

Enrichment Pipeline

Step 1: Assess What's Missing

-- Query the target object to find gaps
SELECT "Name", "Email", "LinkedIn URL", "Company", "Title", "Location"
FROM v_leads
WHERE "Email" IS NULL OR "LinkedIn URL" IS NULL OR "Title" IS NULL;

Step 2: Prioritize by Value

  • High priority: Missing email (needed for outreach)
  • Medium priority: Missing title/company (needed for personalization)
  • Low priority: Missing education, connections count, about text

Step 3: Enrich Per Record

For each record with gaps:

If LinkedIn URL is known but other fields missing:

  1. Use linkedin-scraper to visit profile
  2. Extract: title, company, location, education, about
  3. Update DuckDB record

If LinkedIn URL is missing:

  1. Search LinkedIn: {name} {company} or {name} {title}
  2. Verify match (name + company alignment)
  3. Store LinkedIn URL, then scrape full profile

If Email is missing:

  1. Find company domain (web search or LinkedIn company page)
  2. Try common patterns:

- first@domain.com - first.last@domain.com - flast@domain.com - firstl@domain.com

  1. Optionally verify with web search: "email" "{name}" site:{domain}
  2. Check company team/about page for email format clues

If Company info is missing:

  1. Web search: "{name}" "{title}" or check LinkedIn
  2. Fetch company website for: industry, size, description, funding

Step 4: Update Records

-- Update via DuckDB pivot view
UPDATE v_leads SET
  "Email" = ?,
  "LinkedIn URL" = ?,
  "Title" = ?,
  "Company" = ?,
  "Location" = ?
WHERE id = ?;

Bulk Enrichment Mode

For enriching many records at once:

  1. Query all incomplete records from DuckDB
  2. Group by company (scrape company once, apply to all employees)
  3. Process in batches of 10-20 records
  4. Report progress after each batch:
   Enrichment Progress: 45/120 leads (38%)
   ├── Emails found: 32/45 (71%)
   ├── LinkedIn matched: 41/45 (91%)
   ├── Titles updated: 38/45 (84%)
   └── ETA: ~15 min remaining
  1. Save checkpoint after each batch (in case of interruption)

Enrichment Quality Rules

  • Confidence scoring: Mark each enriched field with confidence (high/medium/low)

- High: Direct match from LinkedIn profile or company website - Medium: Inferred from patterns (email format) or partial match - Low: Best guess from web search results

  • Never overwrite existing data unless explicitly asked
  • Flag conflicts: If enriched data contradicts existing data, flag for review
  • Dedup check: Before inserting LinkedIn URL, check it's not already assigned to another contact

Email Pattern Discovery

Common corporate email formats by frequency:

  1. first.last@domain.com (most common, ~45%)
  2. first@domain.com (~20%)
  3. flast@domain.com (~15%)
  4. firstl@domain.com (~10%)
  5. first_last@domain.com (~5%)
  6. last.first@domain.com (~3%)
  7. first.l@domain.com (~2%)

Strategy:

  1. If you know one person's email at the company, derive the pattern
  2. Search web for "@{domain}" email format
  3. Check company team page source code for mailto: links
  4. Use the most common pattern as fallback

Output

After enrichment, provide a summary:

Enrichment Complete: 120 leads processed
├── Emails: 94 found (78%), 26 still missing
├── LinkedIn: 108 matched (90%), 12 not found
├── Titles: 115 updated (96%)
├── Companies: 118 confirmed (98%)
├── Locations: 89 found (74%)
└── Avg confidence: High (82%), Medium (14%), Low (4%)

Top gaps remaining:
- 26 leads missing email (mostly small/stealth companies)
- 12 leads missing LinkedIn (common names, ambiguous matches)

DuckDB Field Mapping

Standard field names for Ironclaw CRM objects:

Enrichment DataDuckDB FieldType
Full nameNametext
Email addressEmailemail
LinkedIn URLLinkedIn URLurl
Job titleTitletext
Company nameCompanytext / relation
LocationLocationtext
EducationEducationtext
PhonePhonephone
Company sizeCompany Sizetext
IndustryIndustrytext
Enrichment dateEnriched Atdate
ConfidenceEnrichment Confidenceenum (high/medium/low)

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

85.6%
按下载量换算5,417

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills