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Agent Skill · 研究检索

sales-operations(销售业务)

sales-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。

sales-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,权限为只读;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 34,935。

总安装 2,164周安装 92GitHub Stars 4下载 758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:sales-operations(销售业务)
来源仓库:https://github.com/dengineproblem/agents-monorepo
仓库路径:skills/sales-operations
安装命令:
npx skills add https://github.com/dengineproblem/agents-monorepo --skill sales-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 sales-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。

销售流程标准化、系统配置与数据分析的专业能力。设计 stages、概率与字段以确保 pipeline 可视可控。适用于 CRM 治理、绩效看板与过程质量管控。需与销售团队共建 stage definition 与 exit criteria。

sales-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/sales-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 sales-o…;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

sales-operations 怎么安装?

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

sales-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。

sales-operations 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

sales-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。

sales-operations 用的人多吗?

公开数据是累计安装 2,164 次,近一周安装 92 次,下载 758 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。

sales-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。
  • 标注为只读权限,试用阶段不容易误改本地文件。

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。
  • 只想先试试效果、不希望它改动本地文件的人。

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
sales-operations

销售业务 · 本页

2,1644只读未明确通过

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

Sales Operations Expert

Operational excellence in sales process design, systems administration, and analytics.

Sales Process Design

sales_stages:
  stage_0_prospecting:
    name: "Prospecting"
    owner: "SDR"
    probability: "0%"
    activities:
      - "Account research"
      - "Contact identification"
      - "Initial outreach"
    exit_criteria:
      - "Meeting scheduled"
      - "Interest confirmed"
    required_fields:
      - "Lead source"
      - "ICP score"

  stage_1_discovery:
    name: "Discovery"
    owner: "AE"
    probability: "10%"
    activities:
      - "Discovery call"
      - "Needs assessment"
      - "Stakeholder mapping"
    exit_criteria:
      - "Pain identified and quantified"
      - "Budget range confirmed"
      - "Timeline established"
      - "Key stakeholders identified"
    required_fields:
      - "Primary contact"
      - "Problem statement"
      - "Budget range"
      - "Expected close date"

  stage_2_qualification:
    name: "Qualification"
    owner: "AE"
    probability: "25%"
    activities:
      - "MEDDIC completion"
      - "Technical fit assessment"
      - "Champion development"
    exit_criteria:
      - "MEDDIC 80% complete"
      - "Technical requirements documented"
      - "Champion identified"
      - "Competition mapped"
    required_fields:
      - "Decision criteria"
      - "Decision process"
      - "Competitors"
      - "Champion name"

  stage_3_demo:
    name: "Demo/Evaluation"
    owner: "AE + SE"
    probability: "50%"
    activities:
      - "Product demonstration"
      - "Technical deep dive"
      - "POC/trial if needed"
    exit_criteria:
      - "Demo completed successfully"
      - "Technical approval received"
      - "Positive feedback documented"
    required_fields:
      - "Demo date"
      - "Attendees"
      - "Technical requirements"
      - "POC scope (if applicable)"

  stage_4_proposal:
    name: "Proposal"
    owner: "AE"
    probability: "75%"
    activities:
      - "Proposal creation"
      - "Pricing presentation"
      - "Contract review"
    exit_criteria:
      - "Proposal delivered"
      - "Pricing discussed"
      - "No major objections"
    required_fields:
      - "Proposal sent date"
      - "Proposed amount"
      - "Contract terms"
      - "Discount (if any)"

  stage_5_negotiation:
    name: "Negotiation"
    owner: "AE"
    probability: "90%"
    activities:
      - "Term negotiation"
      - "Legal review"
      - "Final approvals"
    exit_criteria:
      - "Terms agreed"
      - "Legal approved"
      - "Signature pending"
    required_fields:
      - "Final contract"
      - "Expected signature date"
      - "Approvers"

  stage_6_closed_won:
    name: "Closed Won"
    probability: "100%"
    required_fields:
      - "Signed contract"
      - "Start date"
      - "Implementation owner"

CRM Management

crm_administration:
  data_model:
    objects:
      lead:
        purpose: "Pre-qualified prospects"
        key_fields:
          - "Name, Company, Email"
          - "Lead source"
          - "Lead score"
          - "Status"
        lifecycle: "Create → Qualify → Convert to Contact/Opp"

      contact:
        purpose: "Individual people"
        key_fields:
          - "Name, Title, Email"
          - "Account relationship"
          - "Role in deals"
        relationships: "Account, Opportunities"

      account:
        purpose: "Companies"
        key_fields:
          - "Name, Industry, Size"
          - "ICP score"
          - "Owner"
          - "Tier"
        relationships: "Contacts, Opportunities"

      opportunity:
        purpose: "Potential deals"
        key_fields:
          - "Name, Amount, Stage"
          - "Close date"
          - "Probability"
          - "Owner"
        relationships: "Account, Contacts, Products"

  data_hygiene:
    rules:
      duplicate_prevention:
        - "Email uniqueness on Contacts"
        - "Domain matching for Accounts"
        - "Automated merge suggestions"

      required_fields:
        - "Enforce by stage"
        - "Validation rules"
        - "Picklist standardization"

      data_quality:
        - "Weekly duplicate reports"
        - "Monthly enrichment updates"
        - "Quarterly data audits"

  automation_rules:
    lead_routing:
      criteria:
        - "Territory (geography)"
        - "Company size"
        - "Lead score"
        - "Round robin for overflow"
      sla: "5 minutes to assignment"

    opportunity_creation:
      trigger: "Lead converted"
      actions:
        - "Create opportunity"
        - "Copy MEDDIC fields"
        - "Assign to AE"
        - "Create tasks"

    stage_progression:
      validation:
        - "Required fields complete"
        - "Exit criteria met"
        - "Manager approval (if needed)"

Forecasting

forecast_methodology:
  categories:
    commit:
      definition: "Will close this period"
      confidence: ">90%"
      criteria:
        - "Verbal yes"
        - "Contract in legal"
        - "No blockers"
      weighting: "100%"

    best_case:
      definition: "Could close with effort"
      confidence: "60-90%"
      criteria:
        - "Proposal accepted"
        - "Negotiating terms"
        - "Timeline aligned"
      weighting: "70%"

    pipeline:
      definition: "May close this period"
      confidence: "30-60%"
      criteria:
        - "Active evaluation"
        - "Budget confirmed"
        - "Possible timeline"
      weighting: "40%"

    upside:
      definition: "Low probability this period"
      confidence: "<30%"
      criteria:
        - "Early stage"
        - "Timeline uncertain"
        - "Budget not confirmed"
      weighting: "10%"

  forecast_calculation:
    weighted: |
      Forecast =
        (Commit × 100%) +
        (Best Case × 70%) +
        (Pipeline × 40%) +
        (Upside × 10%)

    coverage: |
      Coverage Ratio = Total Pipeline / Quota
      Target: 3-4x coverage

  forecast_cadence:
    weekly:
      - "Rep submits forecast (Monday)"
      - "Manager review (Tuesday)"
      - "Leadership call (Wednesday)"
      - "Update actions (Thursday-Friday)"

    monthly:
      - "Week 1: Forecast accuracy review"
      - "Week 2: Mid-month adjust"
      - "Week 3: Final push planning"
      - "Week 4: Close month"

  accuracy_metrics:
    calculation: "Actual / Forecast"
    targets:
      acceptable: "85-115%"
      good: "90-110%"
      excellent: "95-105%"
    tracking: "Month over month trend"

Pipeline Analytics

pipeline_metrics:
  volume:
    total_pipeline: "Sum of all open opportunities"
    new_pipeline: "Created this period"
    pipeline_growth: "(Current - Previous) / Previous"

  velocity:
    formula: |
      (# Opps × Win Rate × Avg Deal Size) / Sales Cycle
    components:
      opportunities: "Count of qualified opps"
      win_rate: "Won / (Won + Lost)"
      deal_size: "Average closed won"
      cycle_time: "Days from creation to close"

  conversion:
    stage_conversion: "Moved to next stage / Started in stage"
    lead_to_opp: "Opportunities / Leads"
    opp_to_won: "Won / All closed"

  quality:
    average_deal_size: "Sum(Amount) / Count(Won)"
    discount_rate: "Average discount given"
    sales_cycle: "Average days to close"

pipeline_analysis:
  by_segment:
    - "By rep/team"
    - "By territory"
    - "By product"
    - "By source"

  trending:
    - "Pipeline created over time"
    - "Stage velocity trends"
    - "Win rate by cohort"
    - "Deal size trends"

  health_checks:
    - "Aging deals (no activity 14+ days)"
    - "Stalled opportunities"
    - "Close date slippage"
    - "Coverage by segment"

Deal Desk Operations

deal_desk:
  approval_matrix:
    standard_deal:
      criteria: "Within guidelines"
      approver: "AE manager"
      turnaround: "Same day"

    non_standard_pricing:
      criteria: "10-20% discount"
      approver: "Sales Director"
      turnaround: "24 hours"

    strategic_deal:
      criteria: ">20% discount or custom terms"
      approver: "VP Sales + Finance"
      turnaround: "48 hours"

    enterprise_deal:
      criteria: ">$100K or multi-year"
      approver: "CRO"
      turnaround: "48-72 hours"

  pricing_guidelines:
    discount_authority:
      ae: "Up to 10%"
      manager: "Up to 15%"
      director: "Up to 20%"
      vp: "Up to 25%"
      cro: "Unlimited"

    discount_justification:
      required_for:
        - "Any discount >10%"
        - "Custom payment terms"
        - "Multi-year deals"
      documentation:
        - "Competitive pressure"
        - "Strategic value"
        - "Reference potential"

  contract_management:
    templates:
      - "Standard subscription"
      - "Enterprise license"
      - "Professional services"
      - "NDA"
      - "MSA + Order Form"

    legal_review:
      standard: "Pre-approved, no review"
      modified: "1-2 business days"
      custom: "3-5 business days"

    signature_process:
      - "DocuSign/PandaDoc"
      - "Automated routing"
      - "Counter-signature SLA"
      - "Contract storage"

Performance Analytics

sales_dashboards:
  executive:
    metrics:
      - "Revenue vs target"
      - "Pipeline coverage"
      - "Win rate trend"
      - "Forecast accuracy"
      - "Headcount vs plan"
    refresh: "Daily"

  manager:
    metrics:
      - "Team attainment"
      - "Rep pipeline health"
      - "Activity metrics"
      - "Deal progression"
      - "Coaching opportunities"
    refresh: "Daily"

  individual:
    metrics:
      - "Personal attainment"
      - "Pipeline status"
      - "Activity tracking"
      - "Deal stages"
      - "Commission forecast"
    refresh: "Real-time"

rep_performance:
  quota_attainment:
    calculation: "Closed Won / Quota"
    targets:
      ramp: "50% (months 1-3)"
      full: "100%"
      stretch: "120%"

  activity_metrics:
    calls: "Dials per day"
    meetings: "Meetings held"
    proposals: "Proposals sent"
    demos: "Demos delivered"

  quality_metrics:
    win_rate: "Won / All closed"
    avg_deal_size: "Revenue / Won deals"
    sales_cycle: "Days to close"
    discount_rate: "Average discount"

  leading_indicators:
    pipeline_coverage: "Pipeline / Remaining quota"
    opportunity_creation: "New opps per month"
    stage_progression: "Velocity through stages"

Territory & Quota

territory_management:
  models:
    geographic:
      basis: "Region, country, state"
      pros: "Simple, clear ownership"
      cons: "Uneven potential"

    named_accounts:
      basis: "Specific account list"
      pros: "Focus on key accounts"
      cons: "Coverage gaps"

    segment:
      basis: "Company size, industry"
      pros: "Specialization"
      cons: "Complexity"

    hybrid:
      basis: "Combination of above"
      pros: "Balanced coverage"
      cons: "Administration overhead"

  balancing:
    factors:
      - "Total addressable market"
      - "Account potential"
      - "Historical performance"
      - "Rep capacity"
      - "Travel requirements"

    metrics:
      - "Accounts per rep"
      - "Potential revenue"
      - "Win rate by territory"

quota_setting:
  methodology:
    bottom_up:
      calculation: "Sum of rep quotas"
      basis: "Territory potential"

    top_down:
      calculation: "Company target / Reps"
      basis: "Growth objectives"

    blended:
      calculation: "Average of both"
      adjustments: "Territory factors"

  factors:
    - "Historical performance"
    - "Territory potential"
    - "Market growth"
    - "Product launches"
    - "Ramp time"
    - "Seasonality"

  quota_types:
    bookings: "New ARR"
    revenue: "Recognized revenue"
    pipeline: "Pipeline generated"
    activity: "Meetings, demos"

Лучшие практики

  1. Process before tools — определи процесс, потом автоматизируй
  2. Data quality first — мусор на входе = мусор на выходе
  3. Inspect what you expect — регулярные ревью pipeline
  4. Forecast accuracy focus — точность > оптимизм
  5. Enable, don't police — помогай продавать, не усложняй
  6. Continuous improvement — итерации на основе данных

平台分布

Codex

36.36%
按下载量换算276

Claude

29.22%
按下载量换算221

Cursor

18.9%
按下载量换算143

Gemini CLI

9.62%
按下载量换算73

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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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