Skip to main content
ClaudeWave
ES, Spanish
Skill288 estrellas del repoactualizado 7d ago

product-discovery

Product discovery and market research expert that guides structured validation of product ideas through continuous user research, outcome-driven problem definition, and evidence-based decision making. Use this skill when testing assumptions, conducting competitive analysis, performing user interviews, or assessing market opportunities using frameworks like Jobs to Be Done, the Kano model, and Value Proposition Canvas. Enforces minimum research thresholds and prohibits solution-first thinking in favor of problem-first approaches.

Instalar en Claude Code
Copiar
git clone --depth 1 https://github.com/majiayu000/spellbook /tmp/product-discovery && cp -r /tmp/product-discovery/skills/product-discovery ~/.claude/skills/product-discovery
Después abre una sesión nueva de Claude Code; el skill carga automáticamente.

SKILL.md

# Product Discovery

## Core Principles

- **Continuous Discovery** — Weekly user conversations, not episodic research
- **Outcome-Driven** — Start with outcomes to achieve, not solutions to build
- **Assumption Testing** — Validate risky assumptions before committing resources
- **Co-Creation** — Build with customers, not just for them
- **Data-Driven** — Use evidence over intuition and stakeholder opinions
- **Problem-First** — Deeply understand the problem space before ideating solutions

---

## Hard Rules (Must Follow)

> These rules are mandatory. Violating them means the skill is not working correctly.

### No Solution-First Thinking

**Never start with a solution. Always define the problem and outcome first.**

```markdown
❌ FORBIDDEN:
"We should build a search bar for the product page"
"Let's add AI recommendations"
"Users need a mobile app"

✅ REQUIRED:
"Problem: Users can't find products (40% exit rate on catalog)
Outcome: Reduce exit rate to 20%
Possible solutions:
1. Search bar with filters
2. AI-powered recommendations
3. Better category navigation
4. Visual product browsing"
```

### Evidence-Based Decisions

**Never assume user needs without evidence from real user research.**

```markdown
❌ FORBIDDEN:
- "Users probably want X" (assumption without data)
- "Our competitor has X, so we need it too" (copycat without validation)
- "The CEO thinks we should build X" (HiPPO without evidence)
- "It's obvious users need X" (intuition without validation)

✅ REQUIRED:
- "5 out of 8 interviewed users mentioned X as a pain point"
- "Analytics show 60% of users abandon at step 3"
- "Prototype test: 7/10 users completed task successfully"
- "Survey (n=500): 45% rated feature as 'must have'"
```

### Minimum Interview Threshold

**Never validate a problem with fewer than 5 user interviews per segment.**

```markdown
❌ FORBIDDEN:
- "We talked to 2 users and they loved the idea"
- "One customer requested this feature"
- "Based on a quick chat with sales..."

✅ REQUIRED:
| Segment | Interviews | Key Finding |
|---------|------------|-------------|
| Power Users | 6 | 5/6 struggle with X |
| New Users | 5 | 4/5 drop off at onboarding |
| Churned | 5 | 3/5 cited missing feature Y |

Minimum per segment: 5 interviews
Confidence increases with more interviews
```

### Falsifiable Assumptions

**Every assumption must be testable and falsifiable with clear success criteria.**

```markdown
❌ FORBIDDEN:
- "Users will like the new design" (not falsifiable)
- "This will improve engagement" (no success criteria)
- "The feature will be useful" (vague)

✅ REQUIRED:
| Assumption | Test | Success Criteria | Result |
|------------|------|------------------|--------|
| Users will complete onboarding in new flow | Prototype test with 10 users | >70% completion | TBD |
| Users prefer visual search | A/B test | >10% lift in conversions | TBD |
| Price point is acceptable | Landing page test | >3% conversion | TBD |
```

---

## Quick Reference

### When to Use What

| Scenario | Framework/Tool | Output |
|----------|---------------|--------|
| Validate product idea | Product Opportunity Assessment | Go/no-go decision |
| Size market opportunity | TAM/SAM/SOM | Market size estimates |
| Understand user needs | User Research (interviews, surveys) | User insights, pain points |
| Analyze competition | Competitive Analysis | Competitive landscape map |
| Discover user motivations | Jobs-to-be-Done (JTBD) | Job stories, outcomes |
| Prioritize features | Kano Model | Feature categorization |
| Define value proposition | Value Proposition Canvas | Value prop statement |
| Test product concept | Lean Startup / MVP | Validated learnings |
| Map opportunities | Opportunity Solution Tree | Prioritized opportunities |

---

## Continuous Discovery Habits

### The Product Trio

Discovery is led by three roles working together weekly:

```
Product Manager → Defines outcomes, owns roadmap
Designer        → Explores solutions, tests usability
Engineer        → Assesses feasibility, proposes technical solutions
```

### Weekly Activities

```markdown
## 1. Customer Interviews (Weekly)
- Schedule 3-5 interviews per week minimum
- Mix of current users, churned users, prospects
- Focus on understanding problems, not pitching solutions
- Record and share insights with team

## 2. Assumption Testing (Weekly)
- Identify riskiest assumptions about solutions
- Design quick tests (prototypes, landing pages, fake doors)
- Run experiments with real users
- Measure results against success criteria

## 3. Opportunity Mapping (Ongoing)
- Build opportunity solution tree
- Map customer needs to potential solutions
- Prioritize based on impact and feasibility
- Update as you learn
```

### Discovery vs Delivery

```
Discovery (What to Build)          Delivery (How to Build It)
├─ Customer interviews             ├─ Sprint planning
├─ Prototype testing               ├─ Development
├─ Assumption validation           ├─ QA testing
├─ Market research                 ├─ Deployment
└─ Opportunity assessment          └─ Post-launch monitoring

Key difference: Discovery reduces risk BEFORE committing to build
```

---

## Product Opportunity Assessment

### Marty Cagan's 10 Questions

Before starting any product initiative, answer these questions:

```markdown
## 1. Problem Definition
**What problem are we solving?**
- Be specific and measurable
- Validate it's a real problem (not assumed)

## 2. Target Market
**For whom are we solving this problem?**
- Define specific user segments
- Size the addressable market (TAM/SAM/SOM)

## 3. Opportunity Size
**How big is the opportunity?**
- Revenue potential
- User growth potential
- Strategic value

## 4. Success Metrics
**How will we measure success?**
- Leading indicators (usage, engagement)
- Lagging indicators (revenue, retention)
- Define targets upfront

## 5. Alternative Solutions
**What alternatives exist today?**
- Direct competitors
- Indirect solutions
- Current user workarounds

## 6. Our Advant
agentsmd-optimizeSkill

Audit AND optimize a CLAUDE.md / AGENTS.md instruction file — score it against the five high-leverage patterns, flag anti-patterns, then apply approved fixes in place. Use when the user says 优化 CLAUDE.md / 优化 AGENTS.md / optimize my agent doc / 帮我改 claudemd, or after an audit when they want the fixes applied (not just reported).

agentsmd-scaffoldSkill

Generate or update repository-specific AGENTS.md instruction files from real repo evidence. Use when asked to create, design, scaffold, split, or improve root or scoped AGENTS.md files for Codex/Claude/agent workflows, especially when a repo needs directory-specific rules, validation commands, generated-file boundaries, or a short agent onboarding router.

api-designSkill

REST/GraphQL/gRPC API design best practices. Use when designing APIs, defining contracts, handling versioning. Covers OpenAPI 3.2, GraphQL Federation, gRPC streaming.

app-ui-designSkill

Mobile app UI design expert for iOS and Android. Use when designing app interfaces, creating design systems, ensuring accessibility, or following platform guidelines. Covers Material Design 3, Human Interface Guidelines, color theory, typography, and 2025 trends.

app-user-story-qaSkill

End-to-end app feature inventory and user-story testing workflow with a canonical tracker. Use when the user asks to audit every feature, derive expected behavior from code, test user journeys, or explicitly fix and retest documented UX or logistical defects.

architecture-foundationSkill

Design architecture foundations before implementation. Use when asked to design or refactor architecture, choose Rust/Go crate, package, module, runtime, workflow, or service boundaries, compare mature project architecture, prevent stacked one-off PRs, audit migration debt in existing repos, or produce a spec before coding.

architecture-researchSkill

Evidence-driven architecture research for understanding real systems and making technical decisions. Use when doing architecture landscape studies, source-backed system archaeology, build-vs-buy or adopt/adapt/build decisions, open-source and commercial comparisons, revisiting an earlier architecture choice, or handling requests such as 架构调研, 架构选型, 竞品架构, 技术尽调, 同类方案, 开源替代, how is X built, and what should we learn from X. Do not use for small mechanical changes, market-only discovery, or detailed design after the technology direction is already fixed.

ask-opencliSkill

Ask Grok or Gemini via opencli (browser-session based, no API cost). Use when the user says "问 grok", "问 gemini", "ask grok", "ask gemini", "用 grok 查", "grok 怎么看", "让 gemini 分析", or wants a second opinion from Grok/Gemini without paying API tokens. Routes to opencli which drives the already-logged-in Chrome session.