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Agent Skill · 研究检索

conducting-user-interviews(进行用户访谈)

conducting-user-interviews 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。

conducting-user-interviews 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 47,935。

总安装 710周安装 29GitHub Stars 3下载 230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:conducting-user-interviews(进行用户访谈)
来源仓库:https://github.com/oldwinter/skills
仓库路径:skills/conducting-user-interviews
安装命令:
npx skills add https://github.com/oldwinter/skills --skill conducting-user-interviews
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/oldwinter/skills --skill conducting-user-interviews

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。

conducting-user-interviews 用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词快速定位候选结果。通过 npx skills add 命令从指定仓库安装并使用。使用前需确认权限范围、维护状态,避免触发联网或文件读写操作。

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。

来源仓库内路径:skills/conducting-user-interviews

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/oldwinter/skills --skill conducting-user-inter…;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

conducting-user-interviews 怎么安装?

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

conducting-user-interviews 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。

conducting-user-interviews 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。

conducting-user-interviews 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。

conducting-user-interviews 用的人多吗?

公开数据是累计安装 710 次,近一周安装 29 次,下载 230 次,GitHub 3 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。

conducting-user-interviews 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
conducting-user-interviews

进行用户访谈 · 本页

7103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

Conducting User Interviews

Scope

Covers

  • Planning an interview study that supports a specific product decision
  • Recruiting the right participants (including early adopters when appropriate)
  • Running interviews that capture specific stories and behaviors (not opinions)
  • Synthesizing interviews into actionable insights, opportunities, and next steps
  • Creating a lightweight “customer panel” habit for fast follow-ups

When to use

  • “Create a discussion guide for discovery interviews.”
  • “Recruit and run 8 user interviews about onboarding / activation.”
  • “We need to understand why users switched (or churned) — run switch interviews.”
  • “Help me synthesize interviews into insights + opportunities.”
  • “I’m a PM and need to run customer conversations next week.”

When NOT to use

  • You primarily need quantitative evidence (survey/experiment/analytics) or statistical confidence
  • You’re doing usability testing with task-based evaluation as the main output (different protocol)
  • You’re working with high-risk populations or sensitive topics (medical, legal, minors) without appropriate approvals/training
  • You have no decision to support (you’ll produce anecdotes without impact)

Inputs

Minimum required

  • Product + target user/customer segment (who, context of use)
  • The decision the interviews should inform (e.g., positioning, onboarding redesign, roadmap bet)
  • Interview type: discovery / JTBD switch / churn / concept test (or “recommend”)
  • Target participants (role, behaviors, situation, recency) + “who NOT to interview”
  • Constraints: number of interviews, time box, language/region, recording allowed, incentives (if any)

Missing-info strategy

  • Ask up to 5 questions from references/INTAKE.md.
  • If answers aren’t available, proceed with explicit assumptions and label unknowns.

Outputs (deliverables)

Produce a User Interview Pack in Markdown (in-chat; or as files if requested):

  1. Context snapshot (goal, decision, hypotheses, constraints)
  2. Recruiting plan (channels, outreach copy, scheduling logistics) + screener
  3. Interview guide (script + question bank + probes) + consent/recording plan
  4. Note-taking template + tagging scheme
  5. Synthesis report (themes, evidence, opportunities, recommendations, confidence)
  6. Follow-up plan (thank-you, keep-in-touch, “customer panel” list/cadence)
  7. Risks / Open questions / Next steps (always included)

Templates: references/TEMPLATES.md

Workflow (8 steps)

1) Frame the decision and choose interview type

  • Inputs: Context + references/INTAKE.md.
  • Actions: Define the decision, what you need to learn (unknowns), and pick the interview type (discovery vs switch vs churn vs concept).
  • Outputs: Context snapshot + study intent.
  • Checks: You can answer: “What will we do differently after these interviews?”

2) Define participant criteria (who/when/why) and sampling plan

  • Inputs: Target segment, product context, constraints.
  • Actions: Specify inclusion/exclusion criteria; prioritize recency (recent switch/churn/attempt) when relevant; decide sample mix (e.g., 6 core + 2 edge cases).
  • Outputs: Participant profile + sampling plan.
  • Checks: Criteria are behavior/situation-based (not demographic proxies).

3) Create recruiting plan + screener + outreach copy

  • Inputs: Participant profile; available channels (CRM, support, community, ads, LinkedIn).
  • Actions: Draft outreach messages, a screener, and scheduling logistics. Expect high drop-off; plan volume accordingly.
  • Outputs: Recruiting plan + screener + outreach copy.
  • Checks: Screener screens for the *story* you need (recency, context, alternatives), not “interest in our product.”

4) Draft the interview guide (story-first)

  • Inputs: Interview type + hypotheses/unknowns.
  • Actions: Build a guide that elicits specific stories (“last time…”) and avoids leading questions. Include probes, pivots, and time boxes. Add consent/recording script.
  • Outputs: Interview guide + consent/recording plan.
  • Checks: At least 70% of questions ask about past behavior and concrete examples.

5) Run interviews + capture clean notes (PM/Design present)

  • Inputs: Guide, logistics, notes template.
  • Actions: Run the session, follow the story, and capture verbatims. If possible, have PM + design observe live (or listen to recordings) to avoid secondhand dilution.
  • Outputs: Completed notes per interview + key quotes + immediate highlights.
  • Checks: Each interview yields 2–5 “story moments” (trigger → struggle → workaround → outcome).

6) Debrief immediately and normalize evidence

  • Inputs: Interview notes, recordings/transcripts (if any).
  • Actions: Do a 10–15 min debrief right after each interview: surprises, hypotheses updates, follow-ups. Tag notes consistently.
  • Outputs: Debrief bullets + tagged notes.
  • Checks: Unclear claims are marked as “needs follow-up” instead of treated as facts.

7) Synthesize across interviews into themes and opportunities

  • Inputs: Tagged notes across interviews.
  • Actions: Cluster by outcomes/struggles; capture contradictions; quantify lightly (counts) without over-claiming. Translate insights into opportunities and recommendations with confidence levels.
  • Outputs: Synthesis report + opportunity list.
  • Checks: Every major insight has at least 2 supporting interviews (or is labeled “single anecdote”).

8) Share, decide, follow up, and run the quality gate

  • Inputs: Draft pack.
  • Actions: Produce a shareable readout, propose next steps, and create a lightweight customer panel habit (5–10 engaged users). Run references/CHECKLISTS.md and score with references/RUBRIC.md.
  • Outputs: Final User Interview Pack + Risks/Open questions/Next steps.
  • Checks: Stakeholders can restate (a) key learning, (b) decision implication, (c) what happens next.

Quality gate (required)

Examples

Example 1 (Discovery): “I’m redesigning onboarding for a B2B product. Create a recruiting plan + discussion guide for 8 discovery interviews with new trial users.” Expected: participant criteria, outreach + screener, discovery guide, notes template, synthesis plan, and a ready-to-run pack.

Example 2 (Switch/JTBD): “We lose deals to spreadsheets. Run switch interviews to learn what triggers teams to move off spreadsheets and what they try instead.” Expected: switch interview guide (timeline + forces), recruiting criteria emphasizing recency, and a synthesis structure that outputs ‘push/pull/anxieties/habits’.

Boundary example: “Ask users what features they want and build whatever they say.” Response: redirect to story-based interviewing; clarify decision context; avoid feature-request interviews without behavioral grounding.

平台分布

Codex

33.82%
按下载量换算78

Claude

30.48%
按下载量换算70

Cursor

16.63%
按下载量换算38

Gemini CLI

9.56%
按下载量换算22

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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