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customer-story-builder客户故事构建者

Agent Skill

customer-story-builder 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

222

周安装

9

GitHub Stars

607

下载量

70
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:customer-story-builder(客户故事构建者)
来源仓库:https://github.com/athina-ai/goose-skills
仓库路径:skills/customer-story-builder
安装命令:
npx skills add https://github.com/athina-ai/goose-skills --skill customer-story-builder
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/athina-ai/goose-skills --skill customer-story-builder

简介

客户故事构建者将原始客户反馈转化为案例研究、社交媒体素材与演示文稿。

  • 适用于营销传播、销售支持与产品验证场景,提炼真实用户价值证明。
  • 支持从 Slack 对话、支持工单中提取素材并自动生成多格式输出。
  • 采用结构化叙事框架突出挑战、解决方案与量化成果。
  • 需注意隐私合规,确保使用公开授权或脱敏后的客户内容。

SKILL.md

Customer Story Builder

Turn raw customer signal into a polished case study — plus every derivative format you need. One input (messy transcript or quote), all outputs (case study, one-pager, social snippet, deck slide).

Core principle: The best customer stories already exist in your support tickets, Slack channels, and call recordings. You just need to extract and structure them.

When to Use

  • "Turn this customer interview into a case study"
  • "We have a great Slack quote from [customer] — help me build a story around it"
  • "Write a case study for [customer]"
  • "I need social proof assets from [customer win]"
  • "Package this customer result for the sales team"

Phase 0: Intake

Customer Context

  1. Customer name — Can we use their name publicly? (Named vs. anonymous)
  2. Company description — Industry, size, stage (1 sentence)
  3. Customer role/title — Who's the champion?
  4. How long have they been a customer?

Raw Input (provide any/all)

  1. Interview transcript — Full or partial transcript from a customer call
  2. Slack/email quotes — Specific messages where they praised the product
  3. Survey responses — NPS comments, CSAT feedback
  4. Support ticket excerpts — Before/after of a problem solved
  5. Review excerpts — G2, Capterra, Trustpilot quotes
  6. Metrics — Any numbers: time saved, revenue impact, efficiency gains, before/after

Story Angle

  1. Primary use case — What were they using the product for?
  2. Key transformation — What changed? (The "before → after" in one sentence)
  3. Output formats needed — Full case study, one-pager, social snippet, sales slide, or all?

Phase 1: Extract Story Elements

From the raw inputs, identify and extract:

The Problem (Before)

  • What was the customer's situation before using the product?
  • What specific pain were they experiencing?
  • What had they tried before? (Manual process, competitor, nothing)
  • How bad was it? (Quantify if possible — hours wasted, money lost, deals missed)

The Decision (Why You)

  • Why did they choose your product?
  • What alternatives did they consider?
  • What was the deciding factor?

The Solution (How)

  • Which specific features/capabilities did they use?
  • How did they implement it? (Timeline, effort)
  • Any surprising use cases or creative applications?

The Result (After)

  • Hard metrics — numbers, percentages, time saved, revenue gained
  • Soft outcomes — confidence, team morale, process improvements
  • Before/after comparison — the transformation in concrete terms

Best Quotes

Pull the 3-5 strongest verbatim quotes from the raw input:

  • Hero quote — the single most powerful statement (for headlines)
  • Problem quote — describes the pain vividly
  • Result quote — describes the outcome with specificity
  • Recommendation quote — would they recommend? Why?

Phase 2: Generate Story Outputs

Output 1: Full Case Study (800-1200 words)

# [Headline: Outcome-driven, not product-driven]
*[Subhead: Customer name + one-line result]*

---

## About [Customer]

[2-3 sentences: company, industry, size, what they do]

## The Challenge

[2-3 paragraphs: What was the problem? Why did it matter? What had they tried?]

> "[Problem quote]"
> — [Name], [Title] at [Company]

## Why [Your Product]

[1-2 paragraphs: How did they find you? What made them choose you?]

## The Solution

[2-3 paragraphs: How did they use the product? Which capabilities mattered most?]

> "[Solution/experience quote]"

## The Results

[Results summary with metric callouts]

### Key Metrics
- **[Metric 1]:** [Number + context]
- **[Metric 2]:** [Number + context]
- **[Metric 3]:** [Number + context]

> "[Result quote]"

## What's Next

[1 paragraph: Future plans, expansion, what they're excited about]

---

**Industry:** [X] | **Company size:** [X] | **Use case:** [X] | **Product:** [X]

Output 2: One-Pager (Sales Leave-Behind)

# [Customer Name]: [Headline Result]

**Challenge:** [2 sentences]
**Solution:** [2 sentences — what they use and how]
**Results:**
- [Metric 1]
- [Metric 2]
- [Metric 3]

> "[Hero quote]"
> — [Name], [Title]

[CTA: Learn more / Request a demo]

Output 3: Social Proof Snippets

For website testimonial section:

"[Short, punchy quote — max 2 sentences]"
— [Name], [Title] at [Company]
[Result: X% improvement in Y]

For LinkedIn post:

[Customer Name] just shared their results:

→ [Metric 1]
→ [Metric 2]
→ [Metric 3]

"[Quote]"

Here's their story: [link]

For cold email insert:

[Company in their industry] saw [key metric] after switching to [Product].

"[Short quote about the result]" — [Name], [Title]

Output 4: Sales Deck Slide Content

Slide title: "[Customer] — [Key Result]"

Left side:
- Challenge: [1 line]
- Solution: [1 line]
- Result: [1 line with metric]

Right side:
> "[Hero quote]"
— [Name], [Title]

[Customer logo]

Output 5: Metric Callout Cards

For website or marketing collateral:

[BIG NUMBER]
[Label — e.g., "hours saved per week"]
— [Customer Name]

Generate 2-3 of these from the strongest metrics.

Phase 3: Story Quality Check

Before finalizing, verify:

  • Specificity — Are results concrete, not vague? ("3x pipeline" > "improved results")
  • Credibility — Is the customer named? Is the metric believable?
  • Relevance — Does this story match your ICP? Will prospects see themselves?
  • Permission — Flag if customer approval is needed before publishing
  • Freshness — Are the results recent? (>12 months old = less impactful)

Phase 4: Output

Save all assets to clients/<client-name>/product-marketing/customer-stories/[customer-slug]/:

  • case-study-full.md — Complete case study
  • one-pager.md — Sales leave-behind
  • social-snippets.md — All social proof formats
  • slide-content.md — Deck slide content
  • raw-inputs.md — Original source material (for reference)

Cost

ComponentCost
All story generationFree (LLM reasoning)
TotalFree

Tools Required

None. Pure reasoning skill. Takes raw text input and produces structured outputs.

Trigger Phrases

  • "Turn this transcript into a case study"
  • "Build a customer story for [customer]"
  • "Package [customer]'s results as social proof"
  • "Run customer story builder for [customer]"

适合场景

01

用户想查找某类 Agent Skill 时

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

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

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

36.69%
按下载量换算26

Claude

29.19%
按下载量换算20

Cursor

20.08%
按下载量换算14

Gemini CLI

10.49%
按下载量换算7

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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