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Agent Skill · 研究检索

revenue-operations(收入运营)

revenue-operations 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。

revenue-operations 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;许可证信息还不明确,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 37,889。

总安装 1,653周安装 71GitHub Stars 4下载 579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:revenue-operations(收入运营)
来源仓库:https://github.com/dengineproblem/agents-monorepo
仓库路径:skills/revenue-operations
安装命令:
npx skills add https://github.com/dengineproblem/agents-monorepo --skill revenue-operations
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/dengineproblem/agents-monorepo --skill revenue-operations

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。

对齐销售、营销与客户成功以提升整体收入效能。梳理从流量到增购的完整 revenue engine 流程。适用于诊断 pipeline 瓶颈与优化转化环节。依赖跨部门数据打通与统一 metrics 口径。revenue-operations 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/revenue-operations

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/dengineproblem/agents-monorepo --skill revenue…;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

revenue-operations 怎么安装?

在终端执行 npx skills add https://github.com/dengineproblem/agents-monorepo --skill revenue-operation…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

revenue-operations 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。

revenue-operations 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。

revenue-operations 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。

revenue-operations 用的人多吗?

公开数据是累计安装 1,653 次,近一周安装 71 次,下载 579 次,GitHub 4 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。

revenue-operations 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。
  • 需要处理研究检索类任务、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。

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
revenue-operations

收入运营 · 本页

1,6534需要联网未明确通过

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

Revenue Operations Expert

Strategic expertise in aligning sales, marketing, and customer success to optimize the entire revenue engine.

RevOps Framework

revenue_engine:
  flow: "Marketing → SDR → AE → CS → Expansion"

  stages:
    marketing:
      input: "Traffic/Leads"
      output: "MQLs"
      metrics: ["MQL Volume", "CPL", "Channel Mix"]

    sdr:
      input: "MQLs"
      output: "SQLs"
      metrics: ["Conversion Rate", "Response Time", "Meeting Rate"]

    ae:
      input: "SQLs"
      output: "Closed Won"
      metrics: ["Win Rate", "ACV", "Sales Cycle"]

    cs:
      input: "Customers"
      output: "Retained Revenue"
      metrics: ["NRR", "Churn", "NPS"]

    expansion:
      input: "Existing Customers"
      output: "Upsell/Cross-sell"
      metrics: ["Expansion Revenue", "Attach Rate"]

core_principles:
  - "Single source of truth for data"
  - "Process standardization across teams"
  - "Technology enablement"
  - "Predictable revenue growth"

GTM Strategy

gtm_motions:
  sales_led:
    characteristics:
      - "High-touch sales process"
      - "Enterprise focus"
      - "Complex products"
    metrics:
      cac: "$10,000-50,000"
      sales_cycle: "90-180 days"
      acv: "$50,000+"
    team_structure:
      - "SDRs (outbound focus)"
      - "AEs (closers)"
      - "SEs (technical support)"
      - "CSMs (post-sale)"

  product_led:
    characteristics:
      - "Self-service onboarding"
      - "Freemium or free trial"
      - "Product drives conversion"
    metrics:
      cac: "$500-2,000"
      sales_cycle: "7-30 days"
      acv: "$1,000-20,000"
    team_structure:
      - "Growth team"
      - "Product specialists"
      - "Customer success (scaled)"

  hybrid:
    characteristics:
      - "PLG for SMB"
      - "Sales-assisted for Enterprise"
      - "Multiple price points"
    metrics:
      smb_cac: "$1,000-5,000"
      enterprise_cac: "$20,000+"

Revenue Metrics

core_metrics:
  bookings:
    arr: "Annual Recurring Revenue"
    mrr: "Monthly Recurring Revenue"
    tcv: "Total Contract Value"
    acv: "Annual Contract Value"
    formula:
      arr: "Sum of all annual contract values"
      mrr: "ARR / 12"

  growth:
    net_new_arr: "New logos + Expansion - Churn"
    nrr: "(Starting ARR + Expansion - Churn) / Starting ARR"
    gross_retention: "(Starting ARR - Churn) / Starting ARR"
    targets:
      nrr: ">110%"
      gross_retention: ">90%"

  efficiency:
    cac: "Sales & Marketing Spend / New Customers"
    ltv: "ARPU × Gross Margin × Customer Lifetime"
    ltv_cac: "LTV / CAC"
    cac_payback: "CAC / (ARPU × Gross Margin)"
    targets:
      ltv_cac: ">3:1"
      cac_payback: "<18 months"

  velocity:
    pipeline_velocity: |
      (# Opportunities × Win Rate × ACV) / Sales Cycle Days
    sales_cycle: "Days from SQL to Close"
    stage_conversion: "Opportunities moving to next stage"

Process Design

Lead Management

lead_process:
  lead_sources:
    inbound:
      - "Website forms"
      - "Content downloads"
      - "Demo requests"
      - "Free trial signups"
    outbound:
      - "SDR prospecting"
      - "ABM campaigns"
      - "Events"
      - "Partner referrals"

  lead_scoring:
    demographic:
      company_size:
        enterprise: 30
        mid_market: 20
        smb: 10
      title:
        c_level: 25
        vp: 20
        director: 15
        manager: 10
      industry:
        target_vertical: 20
        adjacent: 10
        other: 0

    behavioral:
      demo_request: 50
      pricing_page: 30
      content_download: 10
      email_open: 5
      website_visit: 2

    threshold:
      mql: 50
      sql: 80

  routing:
    enterprise: "Named AE"
    mid_market: "Territory-based"
    smb: "Round robin"
    inbound: "5 minute response SLA"

Opportunity Management

opportunity_stages:
  stage_1_discovery:
    name: "Discovery"
    probability: "10%"
    exit_criteria:
      - "Pain identified"
      - "Budget confirmed"
      - "Timeline established"
    required_fields:
      - "Primary contact"
      - "Problem statement"
      - "Estimated deal size"

  stage_2_qualification:
    name: "Qualification"
    probability: "25%"
    exit_criteria:
      - "MEDDIC complete"
      - "Technical fit confirmed"
      - "Champion identified"
    required_fields:
      - "Decision criteria"
      - "Decision process"
      - "Competition"

  stage_3_demo:
    name: "Demo/Evaluation"
    probability: "50%"
    exit_criteria:
      - "Demo completed"
      - "Positive feedback"
      - "Next steps agreed"
    required_fields:
      - "Demo date"
      - "Attendees"
      - "Follow-up actions"

  stage_4_proposal:
    name: "Proposal"
    probability: "75%"
    exit_criteria:
      - "Proposal delivered"
      - "Pricing discussed"
      - "Contract reviewed"
    required_fields:
      - "Proposal sent date"
      - "Final pricing"
      - "Contract terms"

  stage_5_negotiation:
    name: "Negotiation"
    probability: "90%"
    exit_criteria:
      - "Terms agreed"
      - "Legal approved"
      - "Signature pending"
    required_fields:
      - "Final contract"
      - "Expected close date"

  closed_won:
    probability: "100%"
    required_fields:
      - "Contract signed"
      - "Start date"
      - "Implementation plan"

MEDDIC Framework

meddic:
  metrics:
    question: "What business results are you trying to achieve?"
    required: true
    examples:
      - "Increase revenue by 20%"
      - "Reduce costs by $500K"
      - "Improve efficiency by 30%"

  economic_buyer:
    question: "Who has budget authority?"
    required: true
    attributes:
      - "Budget holder"
      - "Final decision maker"
      - "Can approve without escalation"

  decision_criteria:
    question: "How will you evaluate solutions?"
    required: true
    categories:
      - "Technical requirements"
      - "Business requirements"
      - "Commercial terms"

  decision_process:
    question: "What is your evaluation process?"
    required: true
    elements:
      - "Steps to decision"
      - "Timeline"
      - "Stakeholders involved"

  identify_pain:
    question: "What problem are you solving?"
    required: true
    depth:
      - "Business impact"
      - "Personal impact"
      - "Urgency"

  champion:
    question: "Who will advocate internally?"
    required: true
    criteria:
      - "Has influence"
      - "Has access to EB"
      - "Wants you to win"

Tech Stack Architecture

tech_stack:
  core_systems:
    crm:
      tool: "Salesforce / HubSpot"
      purpose: "System of record"
      integrations: ["All revenue tools"]

    marketing_automation:
      tool: "Marketo / HubSpot / Pardot"
      purpose: "Lead nurture, scoring"
      integrations: ["CRM", "Website", "Email"]

    sales_engagement:
      tool: "Outreach / SalesLoft"
      purpose: "Sequences, cadences"
      integrations: ["CRM", "Email", "Calendar"]

    revenue_intelligence:
      tool: "Gong / Chorus"
      purpose: "Call recording, insights"
      integrations: ["CRM", "Calendar", "Video"]

  supporting_tools:
    data_enrichment:
      - "ZoomInfo"
      - "Clearbit"
      - "Apollo"

    analytics_bi:
      - "Tableau"
      - "Looker"
      - "Mode"

    cpq:
      - "Salesforce CPQ"
      - "DealHub"
      - "PandaDoc"

    customer_success:
      - "Gainsight"
      - "ChurnZero"
      - "Totango"

  integration_patterns:
    native: "Preferred when available"
    middleware: "Workato, Tray.io, Zapier"
    custom: "APIs for complex logic"

Forecasting

forecast_methodology:
  categories:
    commit:
      definition: "Will close this period"
      confidence: ">90%"
      criteria:
        - "Verbal commitment"
        - "Contract in legal"
        - "No blockers"

    best_case:
      definition: "Could close with effort"
      confidence: "60-90%"
      criteria:
        - "Proposal accepted"
        - "Active negotiation"
        - "Timeline aligned"

    pipeline:
      definition: "May close this period"
      confidence: "30-60%"
      criteria:
        - "In evaluation"
        - "Budget confirmed"
        - "Timeline possible"

  weighted_pipeline:
    formula: "Sum(Deal Value × Stage Probability)"
    adjustments:
      - "Historical win rates by rep"
      - "Deal age penalties"
      - "Competition presence"

  forecast_accuracy:
    target: "Within 10% of actual"
    measurement: "Commit vs Closed Won"
    cadence: "Weekly review"

Capacity Planning

capacity_model:
  sdr:
    activities_per_day:
      calls: 60
      emails: 100
      linkedin: 30
    output_per_month:
      meetings: 15
      sqls: 10
    quota: "$150K pipeline/month"
    ramp_time: "3 months"

  ae:
    capacity:
      active_opportunities: 25
      new_per_month: 8
    quota: "$1.2M ARR/year"
    ramp_time: "6 months"
    average_deal_size: "$50K"
    win_rate: "25%"

  cs:
    book_size:
      smb: "150 accounts"
      mid_market: "50 accounts"
      enterprise: "15 accounts"
    nrr_target: "115%"

  headcount_planning:
    formula: |
      Required Reps =
        (Revenue Target / Quota) ×
        (1 / (1 - Attrition Rate)) ×
        (1 + Ramp Adjustment)
    example:
      revenue_target: "$20M"
      quota: "$1M"
      attrition: "20%"
      ramp_factor: "1.25"
      required_reps: "31"

Reporting Dashboard

executive_dashboard:
  weekly_metrics:
    - "Pipeline created"
    - "Meetings booked"
    - "Deals won/lost"
    - "Forecast update"

  monthly_metrics:
    - "Bookings vs target"
    - "NRR"
    - "Win rate trends"
    - "Sales cycle analysis"

  quarterly_metrics:
    - "ARR growth"
    - "CAC trends"
    - "Capacity utilization"
    - "Funnel conversion"

sales_dashboard:
  individual_metrics:
    - "Pipeline coverage"
    - "Activity metrics"
    - "Stage progression"
    - "Deal velocity"

  team_metrics:
    - "Leaderboard"
    - "Quota attainment"
    - "Win/loss analysis"

Process Optimization

optimization_areas:
  lead_response:
    current: "30 min average"
    target: "<5 min"
    impact: "2x conversion"
    solution: "Auto-routing + alerts"

  pipeline_coverage:
    current: "2.5x"
    target: "4x"
    impact: "Forecast accuracy"
    solution: "SDR capacity + ABM"

  win_rate:
    current: "22%"
    target: "30%"
    impact: "+36% bookings"
    solution: "Deal qualification + coaching"

  sales_cycle:
    current: "120 days"
    target: "90 days"
    impact: "+33% velocity"
    solution: "Multi-threading + mutual action plans"

Лучшие практики

  1. Single source of truth — CRM как единый источник данных
  2. Process before tools — сначала процесс, потом автоматизация
  3. Data hygiene — качество данных критично
  4. Cross-functional alignment — Sales + Marketing + CS
  5. Predictable forecasting — accuracy >90%
  6. Continuous optimization — итерации на основе данных

平台分布

Codex

35.03%
按下载量换算203

Claude

33.05%
按下载量换算191

Cursor

19.37%
按下载量换算112

Gemini CLI

9.47%
按下载量换算55

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。目前只有一个公开来源,建议同时核对源仓库。

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