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product-discovery产品发现

Agent Skill

product-discovery 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

220

周安装

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GitHub Stars

15

下载量

71
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:product-discovery(产品发现)
来源仓库:https://github.com/yannickyamo/skills
仓库路径:skills/product-discovery
安装命令:
npx skills add https://github.com/yannickyamo/skills --skill product-discovery
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。

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skills.shnpx skills
npx skills add https://github.com/yannickyamo/skills --skill product-discovery

简介

product-discovery 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。

  • 适用于产品发现相关的信息搜索与筛选任务,可结合来源仓库和原始 README 核验具体用法。
  • 通过 npx skills add 命令从 GitHub 仓库安装,支持主流宿主环境集成。
  • 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。

SKILL.md

Product Discovery System

"Discovery without delivery = analysis paralysis. Delivery without discovery = feature factory."

This skill covers the Discovery System — continuously discovering which problems matter and which solutions might work. It maintains a living map of customer opportunities and tests solution ideas before committing engineering resources.

Part of: Modern Product Operating Model — a collection of composable product skills.

Related skills: product-strategy, product-architecture, product-delivery, ai-native-product, product-leadership


When to Use This Skill

Use this skill when:

  • Setting up a weekly discovery rhythm
  • Building or updating an Opportunity Solution Tree (OST)
  • Creating interview snapshots after customer conversations
  • Exploring multiple solution approaches
  • Designing and running assumption tests
  • Synthesizing insights across multiple interviews
  • Running an Opportunity Council meeting

Cadence: Weekly rhythm | Owner: Product Trio (PM + Designer + Tech Lead)


The Problem This Solves

Most teams either:

  1. Do discovery once, then execute for months on stale assumptions
  2. Skip discovery entirely and build what stakeholders request
  3. Do discovery but don't connect it to what actually gets built

The Discovery System creates a weekly rhythm that keeps you close to customers and ensures evidence—not opinions—drives decisions.


Philosophy

Core Beliefs

  1. Weekly rhythm over big research projects — 2-3 interviews per week beats quarterly research sprints
  2. The crossfunctional discovery — Handoffs kill learning
  3. Opportunities are problems, not solutions — "Users need faster onboarding" not "Add a wizard"
  4. Multiple solutions per opportunity — Always explore 3+ options before committing
  5. Test in hours and days, not weeks — If your test takes a month, you're testing too much

What This Framework Rejects

  • Discovery theater (interviews that don't change roadmap)
  • Solution-first thinking
  • PM does interviews alone, hands notes to designers
  • Building the first idea that comes to mind
  • Waiting for perfect data before deciding

Framework Components

1. Continuous Discovery Habits

The Weekly Rhythm (Minimum Viable Discovery)

ActivityFrequencyPurpose
Customer interviews2-3 per weekStay connected to real problems
Synthesis session1 per weekUpdate opportunity map
Assumption test1 per weekValidate before building

Who Does Discovery: The Product Trio

RoleContribution
Product ManagerOwns outcome, facilitates, synthesizes
Product DesignerOwns experience, visualizes, prototypes
Tech LeadOwns feasibility, estimates, identifies constraints
Principle: The trio does discovery together. If the PM does interviews alone and hands notes to designers, you've already lost 50% of the insight.

0→1 Mode:

  • Founder does interviews personally
  • 10-15 interviews before patterns emerge
  • Daily cadence if possible
  • Bias toward speed over rigor

Scaling Mode:

  • Research ops supports logistics
  • Systematic interview quotas by segment
  • Centralized insight repository
  • Quarterly synthesis reports

2. Interview Snapshots

After each interview, create a snapshot (not a transcript). Capture the essence, not every word.

Snapshot Format:

INTERVIEW SNAPSHOT
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Date: [Date]
Participant: [Role, Company type, Context]
Interviewer(s): [Names]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

KEY OPPORTUNITIES (Unmet needs discovered)
• [Opportunity #1]
• [Opportunity #2]
• [Opportunity #3]

KEY QUOTE (In their words)
"[Memorable statement that captures their experience]"

QUICK FACTS
• [Relevant context about their situation]
• [Current workflow or tools]
• [Constraints or requirements]

JOBS TO BE DONE (If surfaced)
• Functional: [Task they're trying to accomplish]
• Emotional: [How they want to feel]
• Social: [How they want to be perceived]

SURPRISES
• [Anything unexpected]
• [Assumptions challenged]

FOLLOW-UPS
• [Questions for next interview]
• [Things to validate]

AI Integration for Snapshots:

  • Use AI to draft snapshot from notes
  • Always review — AI misses 20-40% of important context
  • Never let AI replace the act of listening

3. Opportunity Solution Tree (OST)

The OST is your living map connecting outcomes to opportunities to solutions to tests.

Structure:

                    OUTCOME
                    (Metric we're trying to move)
                         │
          ┌──────────────┼──────────────┐
          │              │              │
     OPPORTUNITY    OPPORTUNITY    OPPORTUNITY
     (Unmet need)   (Unmet need)   (Unmet need)
          │              │              │
     ┌────┴────┐    ┌────┴────┐    ┌────┴────┐
     │         │    │         │    │         │
  SOLUTION  SOLUTION SOLUTION SOLUTION SOLUTION SOLUTION
  (Idea)    (Idea)  (Idea)   (Idea)  (Idea)   (Idea)
     │         │
  ┌──┴──┐   ┌──┴──┐
  │     │   │     │
 TEST  TEST TEST  TEST

OST Rules:

RuleWhy
One outcome per treeDon't try to solve everything at once
Opportunities are problems, not solutions"Users struggle to..." not "Add a feature..."
Multiple solutions per opportunityAlways explore 3+ before committing
Evidence-backedEach opportunity has interview/data support
Living documentUpdate weekly as you learn

Good Opportunity Statements:

  • "Users struggle to understand which metrics matter during their first week"
  • "Managers can't quickly see which team members need attention"
  • "New users don't know what to do after signup"

Bad Opportunity Statements (These are solutions):

  • "We need a dashboard"
  • "Add an onboarding wizard"
  • "Send email reminders"

Target Opportunity Selection:

Use compare-and-contrast to select focus:

OpportunityPain SeverityFrequencyStrategic FitEvidence Strength
AHighDailyCore8 interviews
BMediumWeeklyAdjacent3 interviews
CHighMonthlyCore12 interviews
Principle: Choose ONE target opportunity at a time. Complete focus beats scattered effort.

4. Solution Exploration

For every target opportunity, generate at least 3 solution approaches before committing.

The Three Solution Types:

TypeDescriptionExample
The obvious solutionWhat everyone expects"Add an onboarding wizard"
The 10x harder solutionIf effort were no constraint"AI-powered personalized setup"
The non-product solutionPricing, process, partnership, or service"White-glove onboarding call"

Solution Categories:

CategoryWhen to Consider
Product changesFeatures, UX improvements
Pricing/packaging changesHow value is captured
Enablement changesDocumentation, training, support
Process changesHow work gets done internally
Partnership solutionsIntegrate vs. build
Principle: The best solution to a product problem is often not a product change.

Thin-Slice MVP:

Don't build the whole solution. Build the smallest thing that tests your riskiest assumption.

Full SolutionThin Slice
"Complete onboarding wizard with 10 steps, progress tracking, and personalization""Single welcome screen that asks one question and shows one recommendation"
"Full analytics dashboard with customizable widgets""One pre-built view showing the top 3 metrics"
"AI-powered recommendation engine""Rule-based suggestions for top 5 use cases"

5. Assumption Testing

Every solution has assumptions. Find the ones that would kill it if wrong.

Assumption Categories:

CategoryQuestion
DesirabilityWill users want this?
ViabilityWill this work for the business?
FeasibilityCan we build this?
UsabilityCan users figure it out?

Assumption Test Format:

ASSUMPTION TEST
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Assumption: [What we believe is true]
Risk level: [High / Medium / Low]
Test method: [How we'll test]
Success criteria: [What would confirm]
Failure criteria: [What would disprove]
Timebox: [Hours/days, not weeks]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Test Methods (Fastest to Slowest):

MethodTimeWhen to Use
Desk research30 minDoes evidence already exist?
One-question survey1 hourQuick signal from existing users
Fake door test1 dayMeasure interest before building
Concierge test1-3 daysManually deliver the value
Wizard of Oz1 weekFake backend, real frontend
Prototype test1-2 weeksClickable prototype with users
A/B test2-4 weeksLive code, statistical significance
Principle: Test in hours and days, not weeks and months. If your test takes a month, you're testing too much at once.

AI Integration for Testing:

  • Use AI to build prototypes faster (vibe coding)
  • Use AI to analyze survey responses
  • Use AI to synthesize test results
  • Don't use AI to decide — Humans interpret, AI assists

6. Opportunity Council (Scaling Mode)

Weekly cross-functional meeting that turns discovery into decisions. Prevents discovery theater.

Participants:

  • PM (facilitator)
  • Design lead
  • Engineering lead
  • Sales/CS representative (input, not veto)
  • Marketing representative (for GTM alignment)

Agenda (60 min max):

SegmentTimeFocus
New evidence review15 min2-3 key findings from this week
Opportunity prioritization20 minPromote, kill, or park opportunities
Solution shaping15 minReview prototype/test results
GTM/tech flags10 minEarly visibility on constraints

Council Rules:

  • Decisions are recorded with rationale
  • Single decider (PM) — council advises, PM decides
  • No side quests — if it's not on the OST, it waits
  • Evidence required — no "I think users want..."

0→1 Mode: Skip formal council. Founder + team informal sync.


Primary Outputs

OutputDescriptionUpdate Cadence
Opportunity Solution TreeLiving map of outcome → opportunities → solutionsWeekly
Interview snapshotsLibrary of customer evidenceAfter each interview
Test resultsWhat we learned, what we decidedAfter each test
Target opportunityCurrent focus areaWeekly review
Solution candidatesPrototypes ready for prioritizationOngoing

Templates

This skill includes templates in the templates/ directory:

  • interview-snapshot.md — Post-interview capture format
  • opportunity-solution-tree.md — OST structure and rules
  • assumption-test.md — Test design and tracking

Using This Skill with Claude

Ask Claude to:

  1. Set up discovery rhythm: "Help me design a weekly discovery cadence for [team size/stage]"
  2. Create interview guide: "Create an interview guide for understanding [JTBD/opportunity]"
  3. Draft snapshot: "Turn these interview notes into a snapshot"
  4. Build OST: "Help me build an OST for the outcome: [metric]"
  5. Reframe solutions as opportunities: "These are solutions — help me reframe as opportunities"
  6. Generate solution options: "Generate 5 solution approaches for [opportunity]"
  7. Design thin slice: "What's the thin-slice MVP for [solution]?"
  8. Create assumption test: "Design an assumption test for [hypothesis]"
  9. Synthesize interviews: "Find patterns across these [X] interview snapshots"
  10. Prepare Opportunity Council: "Create an agenda for Opportunity Council with these findings"

Connection to Other Skills

When you need to...Use skill
Define ICP and strategic contextproduct-strategy
Convert opportunities to betsproduct-architecture
Plan delivery and measurementproduct-delivery
Discover for AI productsai-native-product
Scale discovery across teamsproduct-leadership

Quick Reference: Discovery Quality Checklist

Before concluding discovery on an opportunity:

  • Evidence breadth — 5+ interviews mentioning this opportunity
  • Evidence depth — Understand functional, emotional, social jobs
  • Multiple solutions explored — 3+ approaches considered
  • Thin slice identified — Know the smallest testable version
  • Riskiest assumption named — Know what would kill this
  • Test designed — Ready to validate before building
  • Strategic fit confirmed — Aligns with strategy canvas

Anti-Patterns to Avoid

Anti-PatternWhy It FailsInstead
Discovery theaterInterviews don't change roadmapEvidence → decisions
AI replaces listeningMiss 40% of insightAI augments, humans decide
Solution-first thinkingBuild wrong thingOpportunity-first
Homer Simpson carFeature bloat from asking "what do you want?"Ask about problems, not solutions
PM does discovery aloneHandoffs kill learningTrio does discovery together
One solution per opportunityMiss better approachesAlways 3+ options
Month-long testsToo slow to learnTest in hours/days

Sources & Influences

  • Teresa Torres — Continuous Discovery Habits, Opportunity Solution Trees
  • Marty Cagan — INSPIRED, EMPOWERED
  • Rob Fitzpatrick — The Mom Test
  • Cindy Alvarez — Lean Customer Development

*Part of the Modern Product Operating Model by Yannick Maurice*

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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

35.25%
按下载量换算25

Claude

29.89%
按下载量换算21

Cursor

19.89%
按下载量换算14

Gemini CLI

10.15%
按下载量换算7

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