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lead-import铅进口

Agent Skill

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。

总安装

642

周安装

27

GitHub Stars

66

下载量

225
CodexClaudeCursorGemini CLI

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

unknown

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: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

简介

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。

SKILL.md

/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

适合场景

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02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

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能力 2

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能力 3

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能力 4

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

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

external-service

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

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来源信息

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