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Agent Skill · 研究检索

customer-persona(客户角色)

customer-persona 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。

customer-persona 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,权限为调用外部服务;许可证为 MIT,暂无第三方扫描结果,按安装量在研究检索类的 73,675 个 Skill 里排第 25,329。

总安装 3,794周安装 190GitHub Stars 2下载 1,651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:customer-persona(客户角色)
来源仓库:https://github.com/skill-zero/s
仓库路径:skills/customer-persona
安装命令:
npx skills add skill-zero/s --skill "customer-persona"
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。

AgentSkills.tonpx skills
npx skills add skill-zero/s --skill "customer-persona"

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。

通过市场数据和头像生成进行研究支持的客户角色创建。涵盖人口统计、心理统计、待完成工作、旅程图和反角色。用于:营销策略、产品开发、用户体验研究、销售支持、内容策略。触发器:客户角色、买家角色、用户角色、目标受众、理想客户、客户概况、受众研究、用户研究、icp、理想客户概况、目标市场、客户头像、受众角色

来源仓库内路径:skills/customer-persona

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 skill-zero/s --skill "customer-persona";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

    它需要调用外部服务,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

customer-persona 怎么安装?

在终端执行 npx skills add skill-zero/s --skill "customer-persona"。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

customer-persona 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。

customer-persona 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

customer-persona 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。

customer-persona 用的人多吗?

公开数据是累计安装 3,794 次,近一周安装 190 次,下载 1,651 次,GitHub 2 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。

customer-persona 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

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。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 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

  • 要求有安全扫描结论才肯安装的团队。
  • 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
customer-persona

客户角色 · 本页

3,7942调用外部服务MIT未收录

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

name
customer-persona
description
Research-backed customer persona creation with market data and avatar generation. Covers demographics, psychographics, jobs-to-be-done, journey mapping, and anti-personas. Use for: marketing strategy, product development, UX research, sales enablement, content strategy. Triggers: customer persona, buyer persona, user persona, target audience, ideal customer, customer profile, audience research, user research, icp, ideal customer profile, target market, customer avatar, audience persona
allowed-tools
Bash(infsh *)

Customer Persona

Create data-backed customer personas with research and visuals via inference.sh CLI.

Quick Start

curl -fsSL https://cli.inference.sh | sh && infsh login

# Research your target market
infsh app run tavily/search-assistant --input '{
  "query": "SaaS product manager demographics pain points 2024 survey"
}'

# Generate a persona avatar
infsh app run falai/flux-dev-lora --input '{
  "prompt": "professional headshot photograph of a 35-year-old woman, product manager, friendly confident expression, modern office background, natural lighting, business casual attire, realistic portrait",
  "width": 1024,
  "height": 1024
}'

Persona Template

┌──────────────────────────────────────────────────────┐
│  [Avatar Photo]                                      │
│                                                      │
│  SARAH CHEN, 34                                      │
│  Product Manager at a Series B SaaS startup          │
│                                                      │
│  "I spend more time making reports than making       │
│   decisions."                                        │
│                                                      │
├──────────────────────────────────────────────────────┤
│  DEMOGRAPHICS          │  PSYCHOGRAPHICS             │
│  Age: 30-38            │  Values: efficiency, data   │
│  Income: $120-160K     │  Personality: analytical,   │
│  Education: BS/MBA     │    organized, collaborative │
│  Location: Urban US    │  Interests: productivity,   │
│  Role: Product/PM      │    leadership, AI tools     │
├──────────────────────────────────────────────────────┤
│  GOALS                 │  PAIN POINTS                │
│  • Ship features       │  • Too many meetings        │
│  faster                │  • Manual reporting (15     │
│  • Data-driven         │    hrs/week)                │
│  decisions             │  • Stakeholder alignment    │
│  • Team alignment      │    is slow                  │
│  • Career growth to    │  • Tool sprawl (8+ apps)   │
│    Director            │  • No single source of      │
│                        │    truth                    │
├──────────────────────────────────────────────────────┤
│  CHANNELS              │  BUYING TRIGGERS            │
│  • LinkedIn (daily)    │  • Peer recommendation      │
│  • Product Hunt        │  • Free trial experience    │
│  • Podcasts (commute)  │  • Integration with Jira    │
│  • Lenny's Newsletter  │  • Team plan pricing        │
│  • Twitter/X           │  • ROI calculator           │
└──────────────────────────────────────────────────────┘

Building a Persona Step-by-Step

Step 1: Research

Start with data, not assumptions.

# Market demographics
infsh app run tavily/search-assistant --input '{
  "query": "product manager salary demographics 2024 survey report"
}'

# Pain points and challenges
infsh app run exa/search --input '{
  "query": "biggest challenges facing product managers SaaS companies"
}'

# Tool usage patterns
infsh app run tavily/search-assistant --input '{
  "query": "most popular tools product managers use 2024 survey"
}'

# Content consumption habits
infsh app run exa/answer --input '{
  "question": "Where do product managers get their industry news and professional development?"
}'

Step 2: Demographics

Use ranges, not exact values. Personas represent a segment, not one person.

FieldFormatExample
Age rangeX-Y30-38
Income range$X-$Y$120,000-$160,000
EducationCommon degreesBS Computer Science, MBA
LocationRegion/typeUrban US, major tech hubs
Job titleRole levelSenior PM, Product Lead
Company sizeRange50-500 employees
IndustrySectorB2B SaaS

Step 3: Psychographics

What they think, value, and believe.

CategoryQuestions to Answer
ValuesWhat matters most to them professionally?
AttitudesHow do they feel about their industry's direction?
MotivationsWhat drives them at work?
PersonalityAnalytical vs intuitive? Leader vs collaborator?
InterestsWhat do they read/watch/listen to professionally?
LifestyleWork-life balance preference? Remote/hybrid/office?

Step 4: Goals

What they're trying to achieve (both professional and personal).

Professional:
- Ship features faster with fewer meetings
- Make data-driven decisions (not gut feelings)
- Get promoted to Director of Product within 2 years
- Build a more autonomous product team

Personal:
- Leave work by 6pm more often
- Be seen as a strategic leader, not a ticket manager
- Stay current with industry trends without information overload

Step 5: Pain Points

Quantify whenever possible. Vague pain = vague persona.

❌ "Has trouble with reporting"
✅ "Spends 15 hours per week creating manual reports for 4 different stakeholders"

❌ "Too many tools"
✅ "Uses 8 different tools daily (Jira, Slack, Notion, Figma, Analytics, Sheets, Docs, Email) with no unified view"

❌ "Meetings are a problem"
✅ "Averages 6 hours of meetings per day, leaving only 2 hours for deep work"

Step 6: Jobs-to-be-Done (JTBD)

Three types of jobs:

Job TypeDescriptionExample
FunctionalThe task they need to accomplish"Prioritize the product backlog based on customer impact data"
EmotionalHow they want to feel"Feel confident presenting to the exec team"
SocialHow they want to be perceived"Be seen as the person who makes data-driven decisions"

Step 7: Buying Process

StageBehavior
AwarenessReads blog posts, sees peer recommendations on LinkedIn
ConsiderationCompares 3-4 tools, reads G2/Capterra reviews, asks in Slack communities
DecisionRequests demo, needs IT/security approval, evaluates team pricing
InfluencersEngineering lead, VP of Product, CFO (for budget)
Objections"Will my team actually adopt it?", "Does it integrate with Jira?"
Trigger eventNew quarter with aggressive goals, new VP demanding better reporting

Step 8: Generate Avatar

# Match demographics: age, gender, ethnicity, professional context
infsh app run falai/flux-dev-lora --input '{
  "prompt": "professional headshot photograph of a 34-year-old Asian American woman, product manager, warm confident smile, modern tech office background, natural lighting, wearing smart casual blouse, realistic portrait photography, sharp focus",
  "width": 1024,
  "height": 1024
}'

Avatar tips:

  • Match the age range, ethnicity representation, and professional context
  • Use "professional headshot photograph" for realistic results
  • Friendly, approachable expression (not stock-photo-stiff)
  • Background suggests their work environment
  • Business casual or industry-appropriate attire

The Anti-Persona

Equally important: who is NOT your customer.

ANTI-PERSONA: "Enterprise Earl"
- CTO at a 5,000+ person enterprise
- Needs SOC 2, HIPAA, on-premise deployment
- 18-month procurement cycles
- Wants white-glove onboarding and dedicated CSM
- WHY NOT: Our product is self-serve SaaS for SMB/mid-market.
  Enterprise needs would require 2+ years of product investment.

Anti-personas prevent wasted effort on customers you can't serve.

Multiple Personas

Most products have 2-4 personas. More than 4 = too many to serve well.

PriorityPersonaRole
PrimaryThe main user and buyerWho you optimize for
SecondaryInfluences the buying decisionWho you need to convince
TertiaryUses the product occasionallyWho you support, not target

Validation

Personas based on assumptions are fiction. Validate with:

MethodWhat You Learn
Customer interviews (5-10)Real language, real pain points
Support ticket analysisActual problems, not assumed ones
Analytics dataActual behavior, not reported behavior
Survey (50+ responses)Quantified patterns across segments
Sales call recordingsObjections, buying triggers, language

Common Mistakes

MistakeProblemFix
Based on assumptionsFiction, not researchStart with data
Too many personas (6+)Can't serve everyone wellMax 3-4
Vague pain pointsNot actionableQuantify everything
Demographics onlyMisses motivations and behaviorAdd psychographics, JTBD
Never updatedBecomes outdatedReview quarterly
No anti-personaWasted effort on wrong customersDefine who you're NOT for
Single persona for allDifferent users have different needsPrimary/secondary/tertiary

Related Skills

npx skills add inference-sh/skills@web-search
npx skills add inference-sh/skills@ai-image-generation
npx skills add inference-sh/skills@prompt-engineering

Browse all apps: infsh app list

平台分布

Claude Code

57.65%
按下载量换算952

Cursor

30.7%
按下载量换算507

安全审计

暂无安全审计结果可展示。

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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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