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Agent Skill · 开发

lead-import(铅进口)

lead-import 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

lead-import 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 14,983。

总安装 642周安装 27GitHub Stars 66下载 225核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:lead-import(铅进口)
来源仓库:https://github.com/indranilbanerjee/digital-marketing-pro
仓库路径:skills/lead-import
安装命令:
npx skills add https://github.com/indranilbanerjee/digital-marketing-pro --skill lead-import
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/indranilbanerjee/digital-marketing-pro --skill lead-import

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合在需要围绕仓库状态、代码变更或协作事项进行整理时使用。可帮助 Agent 梳理项目进展、跟踪任务或生成协作摘要。安装前建议确认权限范围和仓库访问权限。lead-import 属于开发类 Skill,可作为该场景下的辅助能力补充。

注意避免对敏感分支或保护规则执行写操作。

来源仓库内路径:skills/lead-import

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/indranilbanerjee/digital-marketing-pro --skill…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

lead-import 怎么安装?

在终端执行 npx skills add https://github.com/indranilbanerjee/digital-marketing-pro --skill lead-impo…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

lead-import 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

lead-import 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

lead-import 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

lead-import 用的人多吗?

公开数据是累计安装 642 次,近一周安装 27 次,下载 225 次,GitHub 66 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

lead-import 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
lead-import

铅进口 · 本页

64266调用外部服务未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

/dm:lead-import

Purpose

Import leads into the brand's CRM with data validation, deduplication, lead scoring, and proper consent tracking. Supports CSV files, JSON arrays, and manual entry with automatic source attribution. Ensures every imported lead is clean, scored, deduplicated, and compliant before it reaches the sales team — eliminating the manual data hygiene work that slows down lead-to-opportunity conversion. Integrates with the marketing-automation lead scoring framework to classify leads on import, so high-value prospects are routed to sales immediately while lower-scoring leads enter nurture sequences automatically.

Use this command for leads specifically — it applies scoring, lifecycle staging, and nurture enrollment. For general CRM data syncing (contacts, deals, campaigns) without lead scoring, use /dm:crm-sync instead.

Input Required

The user must provide (or will be prompted for):

  • Lead data: CSV file path, JSON array, or manual field entry — must include at minimum an email address or phone number for deduplication and identity resolution
  • Source attribution: Where these leads originated — form name, event name, campaign identifier, landing page URL, ad platform and campaign, partner referral, webinar registration, or manual prospecting
  • Lead scoring threshold (optional): Minimum score for a lead to be imported as marketing-qualified (MQL) — leads below threshold are imported as raw leads with lower priority routing
  • CRM platform: Target CRM — Salesforce, HubSpot, Zoho, or Pipedrive — and the specific object type (Lead, Contact, or platform equivalent)
  • Required fields: Which fields are mandatory for import — email, first name, last name, company, phone, job title, or custom fields specific to the business qualification criteria
  • Consent status: Whether leads have provided opt-in consent, the consent mechanism (single opt-in, double opt-in, legitimate interest, contractual necessity), and applicable privacy regulation (GDPR, CCPA, CASL)
  • Assignment rules (optional): How imported leads should be assigned — round-robin across reps, territory-based by geography, product-line based, company-size tier, or to a specific owner for manual distribution
  • Duplicate handling preference: When a duplicate is found — update existing record with new data, skip the duplicate entirely, merge specific fields (e.g., add new source but keep existing owner), or create a secondary record linked to the original
  • Lead lifecycle stage: Initial status to assign — new lead, marketing-qualified, sales-accepted, or a custom stage in the brand's lifecycle model
  • Tagging and list membership (optional): Tags, lists, or campaigns to associate with imported leads for downstream segmentation and reporting
  • Notification preferences (optional): Whether to notify assigned sales reps about new leads immediately, and via which channel (CRM notification, email, Slack) — with priority flagging for high-scoring MQLs
  • Nurture sequence trigger (optional): Whether to automatically enroll imported leads into an existing nurture sequence based on score tier, source, or lifecycle stage
  • Custom scoring overrides (optional): Manual score adjustments for specific lead sources — e.g., event leads get +20 bonus points, partner referrals get +15 — applied on top of the standard scoring model
  • Import frequency: Whether this is a one-time import or a recurring source — if recurring, specify expected cadence (daily form submissions, weekly event exports, monthly partner lists) for import template creation

Process

  1. Load brand context: Read ~/.claude-marketing/brands/_active-brand.json for the active slug, then load ~/.claude-marketing/brands/{slug}/profile.json. Apply brand voice, compliance rules for target markets (skills/context-engine/compliance-rules.md), and industry context. Also check for guidelines at ~/.claude-marketing/brands/{slug}/guidelines/_manifest.json — if present, load restrictions and relevant category files. Check for agency SOPs at ~/.claude-marketing/sops/. If no brand exists, ask: "Set up a brand first (/dm:brand-setup)?" — or proceed with defaults.
  2. Parse and validate lead data: Read the input data source and validate every record — check email format (RFC 5322), normalize phone numbers to E.164, verify required fields are present, detect encoding issues, identify obviously fake entries (test@test.com, role-based emails like info@), and flag malformed or incomplete records with specific error reasons.
  3. Normalize and enrich fields: Standardize company names, job titles, and geographic data. Apply consistent formatting — title case for names, lowercase for emails, standardized country and state codes. Where possible, infer missing fields from available data (e.g., company domain from email, country from phone prefix).
  4. Check for duplicates per lead: Query the target CRM for existing records matching each lead on email, phone, or composite key. Categorize results as new (no match), exact duplicate (same email and name), fuzzy match (similar name or domain), or enrichment opportunity (existing record with missing fields this lead can fill).
  5. Score leads using lead scoring framework: Apply the marketing-automation lead scoring model from skills/marketing-automation/lead-scoring.md — score based on demographic fit (job title seniority, company size, industry match), behavioral signals (source quality, content engagement, recency of interaction), and engagement potential. Classify each lead as MQL, raw lead, or nurture candidate based on the threshold.
  6. Validate consent and compliance: Check each lead's consent status against compliance rules for the brand's target markets. Verify opt-in mechanism is documented, timestamp consent records, flag leads missing required consent fields, and ensure lawful data processing basis is recorded per applicable regulation (GDPR Article 6, CCPA, CASL).
  7. Prepare CRM-ready payloads with source attribution: Transform validated leads into platform-specific payloads — map fields to CRM schema, attach source attribution (utm_source, utm_medium, utm_campaign), apply assignment rules, set lead status and lifecycle stage, add tags and list memberships, and include lead score as a custom field.
  8. Create approval gate: Assess risk level — medium for fewer than 50 leads, high for 50 or more. Present import preview showing total lead count, valid vs. invalid breakdown, top 5 sample records with scores, scoring distribution (MQL/raw/nurture counts), duplicate summary, compliance status, and any validation warnings.
  9. On approval, import via CRM MCP: Push lead payloads to the target CRM through the platform MCP in batched requests. Handle rate limits with exponential backoff, retry transient failures, apply assignment rules, trigger any CRM-side automation (welcome workflows, rep notifications), and log each lead's import outcome.
  10. Trigger notifications and nurture enrollment: For high-scoring MQLs, send immediate notifications to assigned reps with lead details and recommended next actions. For nurture-qualified leads, enroll in the specified nurture sequence via the email platform MCP. Log all triggered automations.
  11. Verify import integrity: Query the CRM post-import to confirm record counts match expectations. Spot-check 5 randomly selected imported leads to verify field values, scoring data, source attribution, and assignment all transferred correctly.
  12. Return import summary and log results: Compile final results and log the complete import — timestamp, source attribution, record counts, scoring distribution, assignment breakdown, nurture enrollments, notifications sent, errors, and duration — to ~/.claude-marketing/brands/{slug}/logs/lead-import-log.json.

Output

A structured lead import report containing:

  • Import results summary: Total leads processed with breakdown — created, duplicates skipped, duplicates updated/merged, validation errors, and compliance rejections with percentages and counts
  • Lead score distribution: Breakdown of imported leads by score tier — MQL count and percentage, raw lead count, nurture candidates, average score, median score, and highest-scoring leads highlighted
  • Source attribution record: Campaign, medium, source, and content attribution applied to all imported leads — formatted for downstream ROI reporting and marketing-sourced pipeline tracking
  • Validation error report: Leads that failed validation listed with specific field-level errors — malformed email, missing required field, suspected fake entry, phone format issue, or data type mismatch with suggested corrections
  • Deduplication summary: Duplicate leads found with match type (exact/fuzzy), match fields, confidence score, and action taken (updated, skipped, merged, or flagged for manual review) for each pair
  • Compliance audit trail: Consent status for every imported lead — opt-in mechanism, consent timestamp, applicable regulation, lawful basis, and any leads flagged for missing or insufficient consent with remediation steps
  • Assignment summary: How leads were distributed across sales reps — by owner, territory, product line, or score tier — with counts per assignee and any unassigned leads requiring manual routing
  • Nurture enrollment summary: Leads enrolled in nurture sequences — sequence name, enrollment count, expected first touchpoint date, and leads excluded from nurture (already in active sequences or opted out)
  • Notification delivery report: Notifications sent to sales reps — rep name, lead count assigned, delivery channel, delivery status, and any failed notifications with retry recommendations
  • Execution log: Timestamped record of the import process — batch sizes, API responses, retry attempts, rate limit pauses, processing duration, and CRM confirmation IDs for created records
  • Data quality baseline: Field completeness rates across the imported batch — percentage of leads with company, phone, job title, and other optional fields populated, establishing a quality baseline for this source
  • Source quality comparison: If prior imports from this source exist, compare current batch quality against historical averages — validation error rate trend, scoring distribution shift, duplicate rate trend, and field completeness changes over time
  • CRM automation triggers: Any CRM-side workflows triggered by the import — welcome email sends, task creation for reps, lead routing rule execution, and workflow enrollment confirmations
  • Follow-up recommendations: Suggested next steps — trigger additional nurture sequences, alert sales reps to hot MQLs, schedule data quality review in 30 days, configure recurring import for this source, or refine lead scoring thresholds based on import results

Agents Used

  • crm-manager — Lead validation, deduplication, field mapping, CRM schema resolution, lead scoring application, consent verification, assignment rule execution, lifecycle stage setting, nurture enrollment, and import management
  • email-specialist — Nurture sequence enrollment, email deliverability validation (checking imported emails against known bounce and spam trap lists), and engagement-based scoring input

平台分布

Codex

39.52%
按下载量换算89

Claude

30.12%
按下载量换算68

Cursor

19.29%
按下载量换算43

Gemini CLI

8.89%
按下载量换算20

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。目前只有一个公开来源,建议同时核对源仓库。

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