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Agent Skill · 研究检索

discovery-process(发现过程)

discovery-process 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。

discovery-process 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 6,435。

总安装 22,180周安装 915GitHub Stars 3,917下载 7,247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:discovery-process(发现过程)
来源仓库:https://github.com/deanpeters/product-manager-skills
仓库路径:skills/discovery-process
安装命令:
npx skills add https://github.com/deanpeters/product-manager-skills --skill discovery-process
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/deanpeters/product-manager-skills --skill discovery-process

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。

从问题假设到经过验证的解决方案的结构化发现周期,精心策划框架、访谈、综合和实验。

在 3-4 周内指导产品经理完成六个阶段:提出问题、计划研究、进行客户访谈、综合见解、生成和验证解决方案以及做出继续/不继续的决策 强调持续的发现实践(每周 1 次访谈)而不是一次性的研究项目,并在阶段之间制定决策点以进行调整或继续 包括反模式和常见陷阱(引导性问题、跳过面试、分析瘫痪),帮助团队避免“构建它,他们就会来”综合症 将 10 多个组件和交互技能(问题框架画布、发现访谈准备、机会解决方案树、史诗假设、PRD 开发)编排成结构化工作流程,每个阶段都有清晰的输出

来源仓库内路径:skills/discovery-process

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/deanpeters/product-manager-skills --skill disc…;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

discovery-process 怎么安装?

在终端执行 npx skills add https://github.com/deanpeters/product-manager-skills --skill discovery-proc…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

discovery-process 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。

discovery-process 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。

discovery-process 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。

discovery-process 用的人多吗?

公开数据是累计安装 22,180 次,近一周安装 915 次,下载 7,247 次,GitHub 3,917 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。

discovery-process 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。
  • 来源仓库有 3,917 星,维护活跃度相对可查。
  • 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
discovery-process

发现过程 · 本页

22,1803,917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

Purpose

Guide product managers through a complete discovery cycle—from initial problem hypothesis to validated solution—by orchestrating problem framing, customer interviews, synthesis, and experimentation skills into a structured process. Use this to systematically explore problem spaces, validate assumptions, and build confidence before committing to full development—avoiding "build it and they will come" syndrome and ensuring you're solving real customer problems.

This is not a one-time research project—it's a continuous discovery practice that runs in parallel with delivery, typically 1-2 discovery cycles per quarter.

Key Concepts

What is the Discovery Process?

The discovery process (Teresa Torres, Marty Cagan) is a structured approach to exploring problem spaces and validating solutions before building. It consists of:

  1. Frame the Problem — Define what you're investigating and why
  2. Conduct Research — Gather qualitative and quantitative evidence
  3. Synthesize Insights — Identify patterns, pain points, and opportunities
  4. Generate Solutions — Explore multiple solution options
  5. Validate Solutions — Test assumptions through experiments
  6. Decide & Document — Commit to build, pivot, or kill

Why This Works

  • De-risks product decisions: Tests assumptions before expensive builds
  • Customer-centric: Grounds decisions in real customer problems, not internal opinions
  • Iterative: Builds confidence progressively through small experiments
  • Fast learning: Discovers "no-go" signals early, saves wasted effort

Anti-Patterns (What This Is NOT)

  • Not waterfall research: Discovery runs continuously, not once before dev
  • Not user testing: Discovery validates problems; testing validates solutions
  • Not a substitute for shipping: Discovery informs delivery, doesn't replace it

When to Use This

  • Exploring new product/feature areas
  • Investigating retention or churn problems
  • Validating strategic initiatives before roadmap commitment
  • Continuous discovery (weekly customer touchpoints)

When NOT to Use This

  • For well-understood problems (move to execution)
  • When stakeholders have already committed to a solution (address alignment first)
  • For tactical bug fixes or technical debt (no discovery needed)

Facilitation Source of Truth

When running this workflow as a guided conversation, use workshop-facilitation as the interaction protocol.

It defines:

  • session heads-up + entry mode (Guided, Context dump, Best guess)
  • one-question turns with plain-language prompts
  • progress labels (for example, Context Qx/8 and Scoring Qx/5)
  • interruption handling and pause/resume behavior
  • numbered recommendations at decision points
  • quick-select numbered response options for regular questions (include Other (specify) when useful)

This file defines the workflow sequence and domain-specific outputs. If there is a conflict, follow this file's workflow logic.

Application

Use template.md for the full fill-in structure.

This workflow orchestrates 6 phases over 2-4 weeks, using multiple component and interactive skills.


Phase 1: Frame the Problem (Day 1-2)

Goal: Define what you're investigating, who's affected, and success criteria.

Activities

1. Run Problem Framing Canvas

  • Use: skills/problem-framing-canvas/SKILL.md (interactive - MITRE)
  • Participants: PM, design, engineering lead
  • Duration: 120 minutes
  • Output: Problem statement + "How Might We" question

2. Create Formal Problem Statement

  • Use: skills/problem-statement/SKILL.md (component)
  • Participants: PM
  • Duration: 30 minutes
  • Output: Structured problem statement with hypothesis

3. Define Proto-Personas (If Needed)

  • Use: skills/proto-persona/SKILL.md (component)
  • When: If target customer segment is unclear
  • Duration: 60 minutes
  • Output: Hypothesis-driven personas

4. Map Jobs-to-be-Done (If Needed)

  • Use: skills/jobs-to-be-done/SKILL.md (component)
  • When: If customer motivations are unclear
  • Duration: 60 minutes
  • Output: JTBD statements

Outputs from Phase 1

  • Problem hypothesis: "We believe [persona] struggles with [problem] because [root cause], leading to [consequence]."
  • Research questions: 3-5 questions to answer through discovery
  • Success criteria: What would validate/invalidate the problem?

Decision Point 1: Do we have enough context to start research?

If YES: Proceed to Phase 2 (Research Planning)

If NO: Gather existing data first:

  • Review support tickets, churn surveys, NPS feedback
  • Analyze product analytics (drop-off points, usage patterns)
  • Review competitor research, market trends
  • Time impact: +2-3 days

Phase 2: Research Planning (Day 3)

Goal: Design research approach, recruit participants, prepare interview guide.

Activities

1. Prep Discovery Interviews

  • Use: skills/discovery-interview-prep/SKILL.md (interactive)
  • Participants: PM, design
  • Duration: 90 minutes
  • Output: Interview plan with methodology, questions, biases to avoid

2. Recruit Participants

  • Target: 5-10 customers per discovery cycle (Teresa Torres: continuous discovery = 1 interview/week)
  • Segment: Focus on personas from Phase 1
  • Recruitment channels:

- Existing customers (email, in-app prompts) - Churned customers (exit interviews) - Cold outreach (LinkedIn, communities)

  • Incentive: $50-100 gift card or product credit
  • Duration: 2-3 days (parallel with Phase 1)

3. Schedule Interviews

  • Format: 45-60 min per interview (30-40 min conversation + buffer)
  • Timeline: Spread across 1-2 weeks
  • Recording: Get consent, record for synthesis

Outputs from Phase 2

  • Interview guide: 5-7 open-ended questions (Mom Test style)
  • Participant roster: 5-10 scheduled interviews
  • Synthesis plan: How you'll capture and analyze insights

Phase 3: Conduct Research (Week 1-2)

Goal: Gather qualitative evidence through customer interviews.

Activities

1. Conduct Discovery Interviews

  • Methodology: From skills/discovery-interview-prep/SKILL.md (Problem validation, JTBD, switch interviews, etc.)
  • Participants: PM + optional observer (design, eng)
  • Duration: 5-10 interviews over 1-2 weeks
  • Focus areas:

- Past behavior (not hypotheticals): "Tell me about the last time you [experienced this problem]" - Workarounds: "How do you currently handle this?" - Alternatives tried: "Have you tried other solutions? Why did you stop?" - Pain intensity: "How much time/money does this cost you?"

2. Take Structured Notes

  • Template:

- Participant: [Name, role, company size] - Context: [When/where they experience problem] - Actions: [What they do, step-by-step] - Pain points: [Frustrations, blockers] - Workarounds: [Current solutions] - Quotes: [Verbatim customer language] - Insights: [Patterns, surprises]

3. Review Support Tickets & Analytics (Parallel)

  • Support tickets: Tag by theme (onboarding, feature confusion, bugs)
  • Analytics: Identify drop-off points, feature usage, cohort behavior
  • Surveys: Review NPS comments, exit surveys, feature requests

Outputs from Phase 3

  • Interview transcripts: Recorded sessions + detailed notes
  • Support ticket themes: Top 10 issues by frequency
  • Analytics insights: Quantitative data on behavior (e.g., "60% abandon onboarding at step 3")

Decision Point 2: Have we reached saturation?

Saturation = same pain points emerge across 3+ interviews, no new insights

If YES (saturated after 5-7 interviews): Proceed to Phase 4 (Synthesis)

If NO (still learning new things): Schedule 3-5 more interviews

  • Time impact: +1 week

Phase 4: Synthesize Insights (End of Week 2)

Goal: Identify patterns, prioritize pain points, map opportunities.

Activities

1. Affinity Mapping (Thematic Analysis)

  • Method:

- Write each insight/quote on sticky note - Group by theme (e.g., "onboarding confusion," "pricing objections," "mobile access") - Count frequency (how many customers mentioned each theme)

  • Participants: PM, design, optional eng
  • Duration: 90-120 minutes
  • Output: Themed clusters with frequency counts

2. Create Customer Journey Map (Optional)

  • Use: skills/customer-journey-mapping-workshop/SKILL.md (interactive)
  • When: If pain points span multiple phases (discover, try, buy, use, support)
  • Duration: 90 minutes
  • Output: Journey map with opportunities ranked by impact

3. Prioritize Pain Points

  • Criteria:

- Frequency: How many customers mentioned this? - Intensity: How painful is it? (time wasted, money lost, emotional frustration) - Strategic fit: Does solving this align with business goals?

  • Method: Score each pain point (1-5) on frequency, intensity, strategic fit
  • Output: Ranked list of top 3-5 pain points to address

4. Update Problem Statement

  • Use: skills/problem-statement/SKILL.md (component)
  • Refine based on research: Did initial hypothesis hold? Adjust if needed.
  • Output: Validated problem statement

Outputs from Phase 4

  • Affinity map: Themes with frequency counts
  • Top 3-5 pain points: Prioritized by frequency × intensity × strategic fit
  • Customer quotes: 3-5 verbatim quotes per pain point
  • Validated problem statement: Refined based on evidence

Phase 5: Generate & Validate Solutions (Week 3)

Goal: Explore solution options, design experiments, validate assumptions.

Activities

1. Generate Opportunity Solution Tree

  • Use: skills/opportunity-solution-tree/SKILL.md (interactive)
  • Input: Top 3 pain points from Phase 4
  • Participants: PM, design, engineering lead
  • Duration: 90 minutes
  • Output: 3 opportunities, 3 solutions per opportunity, POC recommendation

Alternative: Use Lean UX Canvas

  • Use: skills/lean-ux-canvas/SKILL.md (interactive)
  • When: Prefer hypothesis-driven approach over OST
  • Output: Hypotheses to test, minimal experiments

2. Design Experiments

  • For each solution: Define "What's the least work to learn the next most important thing?"
  • Experiment types:

- Concierge test: Manually deliver solution to 10 customers, observe - Prototype test: Clickable mockup, usability test with 10 users - Landing page test: Fake door test (show feature, measure interest) - A/B test: Build minimal version, test with 50% of users

  • Success criteria: What metric/behavior validates hypothesis?

3. Run Experiments

  • Timeline: 1-2 weeks per experiment
  • Participants: PM + design (for prototypes), eng (for A/B tests)
  • Output: Quantitative and qualitative validation data

Outputs from Phase 5

  • Solution options: 3-9 solutions (3 per opportunity)
  • Experiment results: Did hypothesis validate or invalidate?
  • Customer feedback: Qualitative reactions to prototypes/concepts

Decision Point 3: Did experiments validate solution?

If YES (validated): Proceed to Phase 6 (Decide & Document)

If NO (invalidated):

  • Pivot to next solution option
  • Re-run experiments with adjusted approach
  • Time impact: +1-2 weeks

Phase 6: Decide & Document (End of Week 3-4)

Goal: Commit to build, document decision, communicate to stakeholders.

Activities

1. Make Go/No-Go Decision

  • Criteria:

- Problem validated? (Phase 3-4) - Solution validated? (Phase 5) - Strategic fit? (aligns with business goals) - Feasible? (engineering capacity, technical complexity)

  • Decision:

- GO: Move to roadmap, write epics/stories - PIVOT: Explore alternative solution - KILL: De-prioritize, not worth solving now

2. Define Epic Hypotheses (If GO)

  • Use: skills/epic-hypothesis/SKILL.md (component)
  • Participants: PM
  • Duration: 60 minutes per epic
  • Output: Epic hypothesis statement with success criteria

3. Write PRD (If GO)

  • Use: skills/prd-development/SKILL.md (workflow)
  • Participants: PM
  • Duration: 1-2 days
  • Output: Structured PRD with problem, solution, success metrics

4. Communicate Findings

  • Format: 30-min readout covering:

- Problem validation (Phase 3-4 insights) - Solution validation (Phase 5 experiments) - Recommendation (GO/PIVOT/KILL)

  • Participants: Execs, product leadership, key stakeholders
  • Output: Alignment on next steps

Outputs from Phase 6

  • Decision: GO, PIVOT, or KILL
  • Epic hypotheses: (if GO) Testable epic statements
  • PRD: (if GO) Formal product requirements document
  • Stakeholder alignment: Exec buy-in on recommendation

Complete Workflow: End-to-End Summary

Week 1:
├─ Day 1-2: Frame the Problem
│  ├─ skills/problem-framing-canvas/SKILL.md (120 min)
│  ├─ skills/problem-statement/SKILL.md (30 min)
│  └─ [Optional] skills/proto-persona/SKILL.md, skills/jobs-to-be-done/SKILL.md
│
├─ Day 3: Research Planning
│  ├─ skills/discovery-interview-prep/SKILL.md (90 min)
│  ├─ Recruit participants (2-3 days)
│  └─ Schedule 5-10 interviews
│
└─ Day 4-5: Conduct Research (Start)
   └─ First 2-3 customer interviews

Week 2:
├─ Day 1-3: Conduct Research (Continue)
│  └─ Remaining customer interviews (3-7 more)
│
├─ Day 4-5: Synthesize Insights
│  ├─ Affinity mapping (120 min)
│  ├─ [Optional] skills/customer-journey-mapping-workshop/SKILL.md (90 min)
│  ├─ Prioritize pain points
│  └─ Update problem statement
│
└─ Decision: Reached saturation? (if NO, +1 week more interviews)

Week 3:
├─ Day 1-2: Generate & Validate Solutions
│  ├─ skills/opportunity-solution-tree/SKILL.md (90 min)
│  └─ Design experiments
│
├─ Day 3-5: Run Experiments
│  ├─ Concierge tests, prototypes, or A/B tests
│  └─ Gather validation data
│
└─ Decision: Validated? (if NO, pivot to next solution, +1-2 weeks)

Week 4:
└─ Decide & Document
   ├─ Make GO/NO-GO decision
   ├─ [If GO] skills/epic-hypothesis/SKILL.md (60 min per epic)
   ├─ [If GO] skills/prd-development/SKILL.md (1-2 days)
   └─ Communicate findings (30 min readout)

Total Time Investment:

  • Fast track: 3 weeks (5 interviews, 1 experiment)
  • Typical: 4 weeks (7-10 interviews, 1-2 experiments)
  • Thorough: 6-8 weeks (10+ interviews, multiple experiment rounds)

Examples

See examples/sample.md for a full discovery process example.

Mini example excerpt:

**Problem:** Onboarding drop-off due to jargon
**Insight:** 6/10 users quit at step 3
**Decision:** Go with guided checklist experiment

Common Pitfalls

Pitfall 1: Skipping Customer Interviews

Symptom: Rely only on analytics and support tickets, no qualitative research

Consequence: Miss "why" behind behavior, build wrong solutions

Fix: Always interview 5-10 customers per discovery cycle (even if you have data)


Pitfall 2: Asking Leading Questions

Symptom: "Would you use [feature X] if we built it?"

Consequence: Confirmation bias, customers say "yes" to be polite

Fix: Use Mom Test questions from skills/discovery-interview-prep/SKILL.md (focus on past behavior)


Pitfall 3: Not Reaching Saturation

Symptom: Interview 2-3 customers, declare discovery complete

Consequence: Small sample, not representative

Fix: Continue interviews until same patterns emerge across 3+ customers (typically 5-7 interviews minimum)


Pitfall 4: Analysis Paralysis

Symptom: Spend 6 weeks synthesizing insights, never move to solutions

Consequence: No delivery, team loses momentum

Fix: Time-box discovery to 3-4 weeks; after Phase 6, move to execution


Pitfall 5: Discovery as One-Time Activity

Symptom: Run discovery once before building, then stop

Consequence: Miss evolving customer needs, market changes

Fix: Continuous discovery (Teresa Torres): 1 customer interview per week, ongoing


References

Related Skills (Orchestrated by This Workflow)

Phase 1:

  • skills/problem-framing-canvas/SKILL.md (interactive)
  • skills/problem-statement/SKILL.md (component)
  • skills/proto-persona/SKILL.md (component, optional)
  • skills/jobs-to-be-done/SKILL.md (component, optional)

Phase 2:

  • skills/discovery-interview-prep/SKILL.md (interactive)

Phase 4:

  • skills/customer-journey-mapping-workshop/SKILL.md (interactive, optional)

Phase 5:

  • skills/opportunity-solution-tree/SKILL.md (interactive)
  • skills/lean-ux-canvas/SKILL.md (interactive, alternative)

Phase 6:

  • skills/epic-hypothesis/SKILL.md (component)
  • skills/prd-development/SKILL.md (workflow)

External Frameworks

  • Teresa Torres, *Continuous Discovery Habits* (2021) — Weekly customer touchpoints, OST framework
  • Rob Fitzpatrick, *The Mom Test* (2013) — How to ask good interview questions
  • Marty Cagan, *Inspired* (2017) — Product discovery principles

Dean's Work

  • Productside Blueprint — Strategic discovery process
  • [If Dean has discovery resources, link here]

Skill type: Workflow Suggested filename: discovery-process.md Suggested placement: /skills/workflows/ Dependencies: Orchestrates 10+ component and interactive skills across 6 phases

平台分布

Claude

32.18%
按下载量换算2,332

Codex

31.88%
按下载量换算2,310

Cursor

20.67%
按下载量换算1,498

Gemini CLI

9.98%
按下载量换算723

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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