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Agent Skill · 研究检索

demand-gen-manager(需求生成经理)

demand-gen-manager 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。

demand-gen-manager 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 51,536。

总安装 582周安装 25GitHub Stars 103下载 204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
MIT

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:demand-gen-manager(需求生成经理)
来源仓库:https://github.com/borghei/claude-skills
仓库路径:skills/demand-gen-manager
安装命令:
npx skills add https://github.com/borghei/claude-skills --skill demand-gen-manager
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/borghei/claude-skills --skill demand-gen-manager

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

demand-gen-manager 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。

它提供专家级需求生成管理,涵盖线索获取、campaign 管理和漏斗优化,适用于 B2B 销售 pipeline 增长场景。使用方式包括建立需求漏斗模型、定义 MQL/SAL 标准和优化转化率,支持 A/B 测试和渠道 mix 调整。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等操作。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/demand-gen-manager

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/borghei/claude-skills --skill demand-gen-manag…;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

    它需要需要联网,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

demand-gen-manager 怎么安装?

在终端执行 npx skills add https://github.com/borghei/claude-skills --skill demand-gen-manager。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

demand-gen-manager 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。

demand-gen-manager 需要什么权限?

权限级别是需要联网。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。

demand-gen-manager 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

demand-gen-manager 用的人多吗?

公开数据是累计安装 582 次,近一周安装 25 次,下载 204 次,GitHub 103 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。

demand-gen-manager 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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 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

  • 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。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
demand-gen-manager

需求生成经理 · 本页

582103需要联网MIT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

Demand Generation Manager

Expert-level demand generation for pipeline growth.

Core Competencies

  • Lead generation
  • Campaign management
  • Marketing automation
  • Funnel optimization
  • Account-based marketing
  • Channel management
  • Attribution modeling
  • Revenue marketing

Demand Generation Framework

Demand Funnel

AWARENESS
├── Website visitors
├── Social reach
└── Ad impressions
       │
       ▼
INTEREST
├── Content engagement
├── Email subscribers
└── Event registrants
       │
       ▼
CONSIDERATION
├── MQLs (Marketing Qualified Leads)
├── Content downloads
└── Demo requests
       │
       ▼
INTENT
├── SALs (Sales Accepted Leads)
├── Pricing page visits
└── Free trial starts
       │
       ▼
PURCHASE
├── SQLs (Sales Qualified Leads)
├── Opportunities
└── Closed Won

Funnel Metrics

StageMetricBenchmarkTarget
AwarenessVisitors-100K/mo
InterestEngaged10%15%
MQLConversion5%8%
SALAcceptance60%75%
SQLConversion40%50%
WonWin Rate25%30%

Campaign Management

Campaign Planning Template

# Campaign Plan: [Campaign Name]

## Overview
- Campaign Type: [Webinar/Content/Event/ABM]
- Launch Date: [Date]
- Duration: [Weeks]
- Budget: $[Amount]

## Objectives
- Primary: [Metric] - [Target]
- Secondary: [Metric] - [Target]

## Target Audience
- Segment: [Description]
- ICP fit: [Criteria]
- List size: [Number]

## Offer
- Value proposition: [What they get]
- CTA: [Action to take]
- Landing page: [URL]

## Channels
| Channel | Budget | Target | CPA Goal |
|---------|--------|--------|----------|
| Email | $X | Y leads | $Z |
| Paid Social | $X | Y leads | $Z |
| Paid Search | $X | Y leads | $Z |

## Timeline
| Week | Activity |
|------|----------|
| -2 | Creative development |
| -1 | Asset finalization |
| 0 | Launch |
| 1-4 | Optimization |
| 5 | Analysis |

## Assets Required
- [ ] Landing page
- [ ] Email sequence (X emails)
- [ ] Ad creative (X variants)
- [ ] Content piece
- [ ] Follow-up sequence

## Success Metrics
- Leads: [Target]
- MQLs: [Target]
- Pipeline: $[Target]
- Cost per lead: $[Target]

Campaign Types

Content Campaigns:

  • Ebooks/Whitepapers
  • Research reports
  • Webinars
  • Video series

Event Campaigns:

  • Hosted events
  • Conferences
  • Roadshows
  • Virtual events

ABM Campaigns:

  • Account-specific content
  • Executive outreach
  • Custom experiences
  • Multi-touch sequences

Nurture Campaigns:

  • Onboarding sequences
  • Re-engagement
  • Cross-sell/upsell
  • Lifecycle marketing

Lead Scoring

Scoring Model

LEAD SCORE = Demographic Score + Behavioral Score

DEMOGRAPHIC (Fit) - Max 50 points
├── Company size
│   ├── Enterprise (1000+): 15
│   ├── Mid-market (100-999): 10
│   └── SMB (<100): 5
├── Industry
│   ├── Target industry: 10
│   ├── Adjacent industry: 5
│   └── Other: 0
├── Title/Role
│   ├── Decision maker: 15
│   ├── Influencer: 10
│   └── User: 5
└── Geography
    ├── Primary market: 10
    └── Secondary market: 5

BEHAVIORAL (Interest) - Max 50 points
├── Website activity
│   ├── Pricing page: 15
│   ├── Product pages: 5 each (max 15)
│   └── Blog: 2 each (max 10)
├── Content engagement
│   ├── Gated download: 10
│   ├── Webinar attend: 10
│   └── Video view: 5
├── Email engagement
│   ├── Open: 1
│   └── Click: 3
└── Direct request
    └── Demo/Contact: 25

MQL THRESHOLD: 60 points

Lead Lifecycle

NEW → ENGAGED → MQL → SAL → SQL → OPPORTUNITY → CUSTOMER

Definitions:
- NEW: Known contact, no engagement
- ENGAGED: Has taken meaningful action
- MQL: Meets score threshold
- SAL: Sales accepted, working
- SQL: Sales qualified, opportunity
- OPPORTUNITY: Active deal
- CUSTOMER: Closed won

Marketing Automation

Automation Workflows

Lead Nurture:

Trigger: Downloads ebook
├── Day 0: Thank you email + resource
├── Day 3: Related content
├── Day 7: Case study
├── Day 14: Webinar invite
└── Day 21: Demo offer

Exit conditions:
- Requests demo
- Unsubscribes
- Becomes MQL

Re-engagement:

Trigger: No activity 60 days
├── Day 0: "We miss you" + new content
├── Day 7: Product update
├── Day 14: Special offer
└── Day 21: Final attempt

Exit conditions:
- Engages with any content
- Unsubscribes

Email Performance Benchmarks

MetricPoorAverageGoodExcellent
Open Rate<15%15-20%20-25%>25%
Click Rate<1%1-2%2-4%>4%
CTR<5%5-10%10-15%>15%
Unsubscribe>1%0.5-1%0.2-0.5%<0.2%

Account-Based Marketing

ABM Program Structure

TIER 1: Strategic (1:1)
├── Account count: 10-25
├── Investment: High
├── Personalization: Full custom
└── Tactics: Executive events, custom content

TIER 2: Scale (1:Few)
├── Account count: 50-200
├── Investment: Medium
├── Personalization: Segment-based
└── Tactics: Industry content, targeted ads

TIER 3: Programmatic (1:Many)
├── Account count: 500+
├── Investment: Low per account
├── Personalization: Light
└── Tactics: Intent-based targeting

ABM Metrics

MetricDefinitionTarget
Account Engagement% of accounts engaged70%+
Contact Coverage% of buying committee reached50%+
Pipeline Created$ from target accounts$X
Deal VelocityDays in pipelineReduce by 20%

Attribution & Reporting

Attribution Models

First Touch: 100% to first interaction Last Touch: 100% to last interaction before conversion Linear: Equal credit across all touches Time Decay: More credit to recent touches W-Shaped: 30% first, 30% MQL, 30% opportunity, 10% other

Demand Gen Dashboard

┌─────────────────────────────────────────────────────────────┐
│              Demand Gen Performance - [Month]                │
├─────────────────────────────────────────────────────────────┤
│  Leads         MQLs           Pipeline        Revenue        │
│  5,432         823            $2.4M           $580K          │
│  +15% MoM      +22% MoM       +18% MoM        +12% MoM       │
├─────────────────────────────────────────────────────────────┤
│  Channel Performance                                         │
│  Email: 2,100 leads ($15 CPL)                               │
│  Paid Search: 1,500 leads ($45 CPL)                         │
│  Social: 1,200 leads ($38 CPL)                              │
│  Organic: 632 leads ($0 CPL)                                │
├─────────────────────────────────────────────────────────────┤
│  Campaign Performance                                        │
│  Q4 Webinar Series: 425 MQLs, $890K pipeline                │
│  Ebook Campaign: 312 MQLs, $650K pipeline                   │
└─────────────────────────────────────────────────────────────┘

Reference Materials

  • references/campaign_playbook.md - Campaign execution guide
  • references/lead_scoring.md - Scoring methodology
  • references/automation.md - Marketing automation patterns
  • references/abm_guide.md - ABM program guide

Scripts

# Campaign performance analyzer
python scripts/campaign_analyzer.py --campaign "Q4 Webinar"

# Lead scoring calculator
python scripts/lead_scoring.py --leads leads.csv --model scoring_model.yaml

# Attribution reporter
python scripts/attribution.py --model w-shaped --period Q4

# Funnel analyzer
python scripts/funnel_analyzer.py --data funnel_data.csv

平台分布

Claude Code

26.78%
按下载量换算55

OpenCode

24.24%
按下载量换算49

Gemini CLI

16.55%
按下载量换算34

Antigravity

11.99%
按下载量换算24

github-copilot

6.54%
按下载量换算13

Cursor

3.1%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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。

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