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commercial-account-growth商业账户增长

Agent Skill

commercial-account-growth 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。

总安装

220

周安装

9

GitHub Stars

1

下载量

71
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:commercial-account-growth(商业账户增长)
来源仓库:https://github.com/piperubio/ai-agents
仓库路径:skills/commercial-account-growth
安装命令:
npx skills add https://github.com/piperubio/ai-agents --skill commercial-account-growth
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/piperubio/ai-agents --skill commercial-account-growth

简介

commercial-account-growth 用于系统识别和推进客户账户增长机会,提升咨询客户关系的长效价值。

  • 适用于 B2B 咨询服务中从交付到销售的闭环管理,支持“先获客、再扩张、后推荐”的 Land & Expand 模型。
  • 通过结构化分析初始合作与后续拓展路径,输出可执行的增长策略和推荐机制,辅助商业团队制定扩张计划。
  • 安装前需确认仓库权限、维护状态及是否涉及网络访问或文件操作,建议结合原始 README 进一步验证功能边界。
  • 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。

SKILL.md

Commercial Account Growth

Purpose

Maximize lifetime value of consulting client relationships by systematically identifying and pursuing expansion opportunities. This skill closes the loop between delivery (PM suite) and sales (Commercial suite), ensuring successful projects naturally lead to more engagements.

Key Insight — The Land & Expand Model for Consulting

  • Land: Win an initial engagement (often Phase 0 assessment or a single workstream).
  • Expand: Grow within the account through adjacent workstreams, new service lines, or deeper engagements.
  • Advocate: Turn happy clients into references, case studies, and referral sources.
  • The cost of expanding within an existing account is 5–7× lower than acquiring a new client.

Inputs

  • commercial-state.md — pipeline and account intelligence.
  • Project delivery artifacts (from PM suite): project-state.md, lessons-learned.md, closure-report.md.
  • user_input — account context, relationship status, strategic goals.
  • Optional: client satisfaction data, NPS feedback.

Outputs (Contract)

1. account-growth-plan.md — Per Account

Generate a structured Markdown document with the following sections:

Account Health Assessment

  • Delivery satisfaction: Based on project outcomes, lessons learned.
  • Relationship strength: Champion engagement, exec access, trust level.
  • Revenue trajectory: Current, historical, potential.
  • Strategic alignment: Does this account align with our growth strategy?

Expansion Signals Detected

Scan project delivery data for:

  • Upsell signals: Client asking for more scope, next phases mentioned, new pain discovered during delivery.
  • Cross-sell signals: Adjacent needs identified (e.g., delivered Software, they need Data next).
  • Advocacy signals: Client expressing satisfaction, willing to be referenced, internal champion promoting us.
  • Risk signals: Champion leaving, budget cuts, competitor entering, delivery issues.

Expansion Opportunities (Prioritized)

For each opportunity include: description, service line, estimated value, probability, effort to pursue, recommended approach. Separate quick wins from strategic plays.

Recommended Actions (Next 90 Days)

  • Relationship actions: Exec alignment, QBR, dinner, etc.
  • Technical actions: Assessment of new area, POC, workshop.
  • Commercial actions: Proposal for next phase, cross-sell pitch.

Account Revenue Projection

Current year, next 12 months, 3-year potential. Label all figures as estimates.

2. case-study.md — When Requested or Supported by Closure Data

Follow the STAR framework:

  • Situation: Client context and challenge (anonymizable).
  • Task: What we were engaged to do.
  • Action: How we approached it (methodology, team, approach).
  • Result: Quantified outcomes (metrics, improvements, ROI).

Include: client quote (if available), timeline, team size, technologies used. Produce two versions: detailed (for sales use) and summary (for website/marketing).

3. Updated commercial-state.md

Enrich account intelligence and add new opportunities to pipeline.

Expansion Signal Detection Framework

During Active Projects

  • "Can you also help with…" → immediate upsell opportunity.
  • New stakeholders engaging → wider organizational interest.
  • Client team struggling with adjacent area → cross-sell opportunity.
  • Positive project reviews → advocacy opportunity.

At Project Closure

  • Lessons learned mention future needs → next engagement.
  • Client requests extended support → retainer opportunity.
  • High satisfaction scores → case study and referral opportunity.

Between Engagements

  • Industry changes affecting client → proactive outreach with insight.
  • New leadership at client → re-engagement opportunity.
  • Client mentioned in news (funding, M&A, expansion) → trigger event.

Guardrails

  1. Never push expansion on an unhappy client — fix delivery issues first.
  2. Account growth must be genuinely in the client's interest, not just ours.
  3. Case studies must be approved by the client before any external use.
  4. Do not propose expansion if current project is at risk — focus on delivery.
  5. Cross-sell must be supported by genuine capability, not aspiration.
  6. Revenue projections must be clearly labeled as estimates, not commitments.
  7. Relationship actions must respect the client's time and boundaries.
  8. Always check for non-compete or exclusivity clauses before cross-selling.

Example

Scenario: A 6-month data platform project is completing. During delivery the client's analytics lead mentioned: "We've got all this data now but nobody knows how to build ML models on it."

Expansion signals detected:

  • Cross-sell (Data → AI): Client expressed need for ML capabilities adjacent to delivered data platform.
  • Upsell: Potential Phase 2 for data platform enhancements (data quality, new sources).
  • Advocacy: Project delivered on time, client sponsor praised the team in the retrospective.

Recommended actions:

  1. Schedule a 1-hour ML readiness workshop (technical action — low effort, high signal).
  2. Draft a Phase 2 proposal for data platform enhancements (commercial action).
  3. Request a client quote for a case study on the data platform delivery (advocacy action).
  4. Propose a QBR with the client CTO to discuss data & AI roadmap alignment (relationship action).

Projected value: Current engagement $400K → Phase 2 $200K + ML engagement $350K → 12-month potential $950K.

Resources

references/

  • expansion-playbooks.md: Detailed playbooks for upselling, cross-selling, advocacy, QBRs, account planning, churn prevention, and revenue metrics. Read when executing any specific expansion activity.

适合场景

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02

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03

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能力概览

能力 1

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能力 2

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能力 3

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能力 4

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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

34.77%
按下载量换算25

Claude

31.66%
按下载量换算22

Cursor

17.87%
按下载量换算13

Gemini CLI

8.43%
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

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

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来源信息

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