Token导航 LogoToken导航

Agent Skill · 研究检索

faion-user-researcher(faion 用户研究员)

faion-user-researcher 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。

faion-user-researcher 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,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 64,557。

总安装 297周安装 12GitHub Stars 2下载 93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:faion-user-researcher(faion 用户研究员)
来源仓库:https://github.com/faionfaion/faion-network
仓库路径:skills/faion-user-researcher
安装命令:
npx skills add https://github.com/faionfaion/faion-network --skill faion-user-researcher
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/faionfaion/faion-network --skill faion-user-researcher

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。

用于用户研究与产品验证,涵盖人物画像、访谈执行和价值主张测试。适用于需要 Jobs-to-be-done、痛点挖掘和问题验证的早期产品阶段。通过检查 .aidocs/product_docs/user-personas.md 了解现有用户模型。

安装命令:npx skills add https://github.com/faionfaion/faion-network --skill faion-user-researcher。涉及真人访谈时应遵守隐私协议,匿名化处理敏感信息。

来源仓库内路径:skills/faion-user-researcher

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/faionfaion/faion-network --skill faion-user-re…;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

faion-user-researcher 怎么安装?

在终端执行 npx skills add https://github.com/faionfaion/faion-network --skill faion-user-researcher。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

faion-user-researcher 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。

faion-user-researcher 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。

faion-user-researcher 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。

faion-user-researcher 用的人多吗?

公开数据是累计安装 297 次,近一周安装 12 次,下载 93 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。

faion-user-researcher 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。
  • 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。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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
faion-user-researcher

faion 用户研究员 · 本页

2972只读未明确有提醒

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

Entry point: /faion-net — invoke this skill for automatic routing to the appropriate domain.

User Research Domain Skill

Communication: User's language. Docs: English.

Purpose

User research and validation for product/startup development. Handles personas, user interviews, jobs-to-be-done, pain point mining, problem validation, survey design, and value proposition testing.

Context Discovery

Auto-Investigation

Check these signals before starting user research:

SignalLocationWhat to Check
Existing personas.aidocs/product_docs/user-personas.mdCurrent user archetypes
Pain points.aidocs/product_docs/pain-points.mdKnown user problems
Interview data.aidocs/product_docs/interview-notes/Previous interview findings
JTBD framework.aidocs/product_docs/jobs-to-be-done.mdUser motivations
Value proposition.aidocs/product_docs/value-proposition.mdProblem-solution fit
Survey data.aidocs/product_docs/surveys/Quantitative research
User validation.aidocs/product_docs/problem-validation.mdValidation results
Product specs.aidocs/todo/,.aidocs/in-progress/Current feature development
Analytics.aidocs/product_docs/analytics/User behavior data
Customer feedbackSupport tickets, reviewsReal user complaints/requests

Discovery Questions

- question: "What user research do you need?"
  header: "Research Type"
  multiSelect: false
  options:
    - label: "Build user personas"
      description: "Create user archetypes and profiles"
    - label: "Conduct user interviews"
      description: "Talk to users to understand needs"
    - label: "Identify pain points"
      description: "Research user problems and frustrations"
    - label: "Jobs-to-be-done analysis"
      description: "Understand user motivations and context"
    - label: "Problem validation"
      description: "Validate if problem is worth solving"
    - label: "Value proposition design"
      description: "Define how product solves user problems"

- question: "What stage is your product in?"
  header: "Product Stage"
  multiSelect: false
  options:
    - label: "Idea/concept"
      description: "No product yet, exploring problem space"
    - label: "Pre-launch"
      description: "Building MVP, validating problem-solution fit"
    - label: "Post-launch"
      description: "Have users, optimizing product"

- question: "Do you have access to target users?"
  header: "User Access"
  multiSelect: false
  options:
    - label: "Yes, existing user base"
      description: "Can interview/survey current users"
    - label: "Need to recruit users"
      description: "Will find target users in communities"
    - label: "No users yet"
      description: "Will use secondary research/personas"

- question: "What's your primary research goal?"
  header: "Research Goal"
  multiSelect: false
  options:
    - label: "Understand user needs"
      description: "Discover what problems users have"
    - label: "Validate problem exists"
      description: "Confirm problem is worth solving"
    - label: "Test solution fit"
      description: "Check if product solves user problems"
    - label: "Segment users"
      description: "Identify different user types"

Quick Reference

Research AreaKey Files
Personaspersona-building.md, ai-persona-building.md, audience-segmentation.md
Interviewsuser-interviews.md, user-interviews-methods.md, ai-interview-analysis.md
Pain Pointspain-point-research.md, problem-validation.md
Validationvalidation-methods.md, user-validation-methods.md, problem-validation-2026.md
JTBDjobs-to-be-done.md
Value Propvalue-proposition-design.md
Surveyssurvey-design.md, user-research-at-scale.md
Use Casesuse-case-mapping.md, feature-discovery.md

Decision Tree

If you need...Use
User profilespersona-building.md, ai-persona-building.md
Pain pointspain-point-research.md, problem-validation.md
User motivationsjobs-to-be-done.md
Value propositionvalue-proposition-design.md
Interview structureuser-interviews.md, user-interviews-methods.md
Validate problemproblem-validation.md, validation-methods.md
Survey questionssurvey-design.md
Segment usersaudience-segmentation.md
Map use casesuse-case-mapping.md, feature-discovery.md
Define success metricssuccess-metrics-definition.md

Research Modes

ModeOutputFiles Used
personasuser-personas.mdpersona-building.md, ai-persona-building.md
painspain-points.mdpain-point-research.md, problem-validation.md
validateproblem-validation.mdvalidation-methods.md, problem-validation-2026.md
interviewsinterview-guide.mduser-interviews.md, user-interviews-methods.md
jtbdjobs-to-be-done.mdjobs-to-be-done.md

Methodologies (21)

Persona Building (4)

  • Persona building
  • AI-assisted persona building
  • AI persona building
  • Audience segmentation

User Interviews (4)

  • User interviews
  • User interviews methods
  • AI interview analysis
  • User research at scale

Problem & Pain Points (3)

  • Pain point research
  • Problem validation
  • Problem validation 2026

Validation Methods (3)

  • Validation methods
  • User validation methods
  • Synthetic users

Jobs-to-be-Done (1)

  • Jobs-to-be-done framework

Value & Use Cases (4)

  • Value proposition design
  • Use case mapping
  • Feature discovery
  • Opportunity solution trees

Research Instruments (2)

  • Survey design
  • Success metrics definition

Key Frameworks

FrameworkPurposeFile
JTBDUser motivations & contextjobs-to-be-done.md
Value Prop CanvasProblem-solution fitvalue-proposition-design.md
Mom TestInterview questionsuser-interviews-methods.md
Persona TemplateUser archetypespersona-building.md
Opportunity Solution TreesFeature prioritizationopportunity-solution-trees.md

Output Files

All outputs go to .aidocs/product_docs/:

ModuleOutput File
Personasuser-personas.md
Pain Pointspain-points.md
Validationproblem-validation.md
Interviewsinterview-guide.md
JTBDjobs-to-be-done.md
Value Propvalue-proposition.md
Surveyssurvey-questionnaire.md

Integration

Parent Skill

Orchestrated by faion-researcher skill.

Related Sub-Skills

  • faion-market-researcher - Market sizing, competitors, pricing

Next Steps

After user research complete:

  • UX design → faion-ux-ui-designer
  • Feature specs → faion-sdd
  • Product roadmap → faion-product-manager

*faion-user-researcher v1.0* *Sub-skill of faion-researcher* *21 methodologies | User Research & Validation*

平台分布

Codex

34.48%
按下载量换算32

Claude

27.52%
按下载量换算26

Cursor

18.54%
按下载量换算17

Gemini CLI

9.86%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills