Product team

Competitive Teardown

Tier: POWERFUL
Category: Product Team
Domain: Competitive Intelligence, Product Strategy, Market Analysis

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type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-1 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Teardown Workflow

Follow these steps in sequence to produce a complete teardown:

1. Define competitors — List 2–4 competitors to analyze. Confirm which is the primary focus.
2. Collect data — Use references/data-collection-guide.md to gather raw signals from at least 3 sources per competitor (website, reviews, job postings, SEO, social).
   Validation checkpoint: Before proceeding, confirm you have pricing data, at least 20 reviews, and job posting counts for each competitor.
3. Score using rubric — Apply the 12-dimension rubric below to produce a numeric scorecard for each competitor and your own product.
   Validation checkpoint: Every dimension should have a score and at least one supporting evidence note.
4. Generate outputs — Populate the templates in references/analysis-templates.md (Feature Matrix, Pricing Analysis, SWOT, Positioning Map, UX Audit).
5. Build action plan — Translate findings into the Action Items template (quick wins / medium-term / strategic).
6. Package for stakeholders — Assemble the Stakeholder Presentation using outputs from steps 3–5.

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type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-2 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Scoring Rubric (12 Dimensions, 1-5)

#	Dimension	1 (Weak)	3 (Average)	5 (Best-in-class)
1	Features	Core only, many gaps	Solid coverage	Comprehensive + unique
2	Pricing	Confusing / overpriced	Market-rate, clear	Transparent, flexible, fair
3	UX	Confusing, high friction	Functional	Delightful, minimal friction
4	Performance	Slow, unreliable	Acceptable	Fast, high uptime
5	Docs	Sparse, outdated	Decent coverage	Comprehensive, searchable
6	Support	Email only, slow	Chat + email	24/7, great response
7	Integrations	0-5 integrations	6-25	26+ or deep ecosystem
8	Security	No mentions	SOC2 claimed	SOC2 Type II, ISO 27001
9	Scalability	No enterprise tier	Mid-market ready	Enterprise-grade
10	Brand	Generic, unmemorable	Decent positioning	Strong, differentiated
11	Community	None	Forum / Slack	Active, vibrant community
12	Innovation	No recent releases	Quarterly	Frequent, meaningful

Example completed row (Competitor: Acme Corp, Dimension 3 – UX):

Dimension	Acme Corp Score	Evidence
UX	2	App Store reviews cite "confusing navigation" (38 mentions); onboarding requires 7 steps before TTFV; no onboarding wizard; CC required at signup.

Apply this pattern to all 12 dimensions for each competitor.

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type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-3 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

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type: skill lifecycle: stable inheritance: inheritable name: experiment-designer description: Use when planning product experiments, writing testable hypotheses, estimating sample size, prioritizing tests, or interpreting A/B outcomes with practical statistical rigor. tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Experiment Designer

Design, prioritize, and evaluate product experiments with clear hypotheses and defensible decisions.

When To Use

Use this skill for:

• A/B and multivariate experiment planning
• Hypothesis writing and success criteria definition
• Sample size and minimum detectable effect planning
• Experiment prioritization with ICE scoring
• Reading statistical output for product decisions

Core Workflow

1. Write hypothesis in If/Then/Because format

• If we change [intervention]
• Then [metric] will change by [expected direction/magnitude]
• Because [behavioral mechanism]

2. Define metrics before running test

• Primary metric: single decision metric
• Guardrail metrics: quality/risk protection
• Secondary metrics: diagnostics only

3. Estimate sample size

• Baseline conversion or baseline mean
• Minimum detectable effect (MDE)
• Significance level (alpha) and power

Use:

python3 scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.02 --mde-type absolute

4. Prioritize experiments with ICE

• Impact: potential upside
• Confidence: evidence quality
• Ease: cost/speed/complexity

ICE Score = (Impact * Confidence * Ease) / 10

5. Launch with stopping rules

• Decide fixed sample size or fixed duration in advance
• Avoid repeated peeking without proper method
• Monitor guardrails continuously

6. Interpret results

• Statistical significance is not business significance
• Compare point estimate + confidence interval to decision threshold
• Investigate novelty effects and segment heterogeneity

Hypothesis Quality Checklist

• Contains explicit intervention and audience
• Specifies measurable metric change
• States plausible causal reason
• Includes expected minimum effect
• Defines failure condition

Common Experiment Pitfalls

• Underpowered tests leading to false negatives
• Running too many simultaneous changes without isolation
• Changing targeting or implementation mid-test
• Stopping early on random spikes
• Ignoring sample ratio mismatch and instrumentation drift
• Declaring success from p-value without effect-size context

Statistical Interpretation Guardrails

• p-value < alpha indicates evidence against null, not guaranteed truth.
• Confidence interval crossing zero/no-effect means uncertain directional claim.
• Wide intervals imply low precision even when significant.
• Use practical significance thresholds tied to business impact.

See:

• references/experiment-playbook.md
• references/statistics-reference.md

Tooling

scripts/sample_size_calculator.py

Computes required sample size (per variant and total) from:

• baseline rate
• MDE (absolute or relative)
• significance level (alpha)
• statistical power

Example:

python3 scripts/sample_size_calculator.py \
  --baseline-rate 0.10 \
  --mde 0.015 \
  --mde-type absolute \
  --alpha 0.05 \
  --power 0.8

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type: skill lifecycle: stable inheritance: inheritable name: landing-page-generator description: Generates high-converting landing pages as complete Next.js/React (TSX) components with Tailwind CSS. Creates hero sections, feature grids, pricing tables, FAQ accordions, testimonial blocks, and C... tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Landing Page Generator

Generate high-converting landing pages from a product description. Output complete Next.js/React components with multiple section variants, proven copy frameworks, SEO optimization, and performance-first patterns. Not lorem ipsum — actual copy that converts.

Target: LCP < 1s · CLS < 0.1 · FID < 100ms
Output: TSX components + Tailwind styles + SEO meta + copy variants

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type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-6 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Generation Workflow

Follow these steps in order for every landing page request:

1. Gather inputs — collect product name, tagline, audience, pain point, key benefit, pricing tiers, design style, and copy framework using the trigger format below. Ask only for missing fields.
2. Analyze brand voice (recommended) — if the user has existing brand content (website copy, blog posts, marketing materials), run it through marketing-skill/content-production/scripts/brand_voice_analyzer.py to get a voice profile (formality, tone, perspective). Use the profile to inform design style and copy framework selection:
   • formal + professional → enterprise style, AIDA framework
   • casual + friendly → bold-startup style, BAB framework
   • professional + authoritative → dark-saas style, PAS framework
   • casual + conversational → clean-minimal style, BAB framework
3. Select design style — map the user's choice (or infer from brand voice analysis) to one of the four Tailwind class sets in the Design Style Reference.
4. Apply copy framework — write all headline and body copy using the chosen framework (PAS / AIDA / BAB) before generating components. Match the voice profile's formality and tone throughout.
5. Generate sections in order — Hero → Features → Pricing → FAQ → Testimonials → CTA → Footer. Skip sections not relevant to the product.
6. Validate against SEO checklist — run through every item in the SEO Checklist before outputting final code. Fix any gaps inline.
7. Output final components — deliver complete, copy-paste-ready TSX files with all Tailwind classes, SEO meta, and structured data included.

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-7 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Design Style Reference

Style	Background	Accent	Cards	CTA Button
Dark SaaS	bg-gray-950 text-white	violet-500/400	bg-gray-900 border border-gray-800	bg-violet-600 hover:bg-violet-500
Clean Minimal	bg-white text-gray-900	blue-600	bg-gray-50 border border-gray-200 rounded-2xl	bg-blue-600 hover:bg-blue-700
Bold Startup	bg-white text-gray-900	orange-500	shadow-xl rounded-3xl	bg-orange-500 hover:bg-orange-600 text-white
Enterprise	bg-slate-50 text-slate-900	slate-700	bg-white border border-slate-200 shadow-sm	bg-slate-900 hover:bg-slate-800 text-white

Bold Startup headings: add font-black tracking-tight to all <h1>/<h2> elements.

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-8 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Representative Component: Hero (Centered Gradient — Dark SaaS)

Use this as the structural template for all hero variants. Swap layout classes, gradient direction, and image placement for split, video-bg, and minimal variants.

export function HeroCentered() {
  return (
    <section className="relative flex min-h-screen flex-col items-center justify-center overflow-hidden bg-gray-950 px-4 text-center">
      <div className="absolute inset-0 bg-gradient-to-b from-violet-900/20 to-transparent" />
      <div className="pointer-events-none absolute -top-40 left-1/2 h-[600px] w-[600px] -translate-x-1/2 rounded-full bg-violet-600/20 blur-3xl" />
      <div className="relative z-10 max-w-4xl">
        <div className="mb-6 inline-flex items-center gap-2 rounded-full border border-violet-500/30 bg-violet-500/10 px-4 py-1.5 text-sm text-violet-300">
          <span className="h-1.5 w-1.5 rounded-full bg-violet-400" />
          Now in public beta
        </div>
        <h1 className="mb-6 text-5xl font-bold tracking-tight text-white md:text-7xl">
          Ship faster.<br />
          <span className="bg-gradient-to-r from-violet-400 to-pink-400 bg-clip-text text-transparent">
            Break less.
          </span>
        </h1>
        <p className="mx-auto mb-10 max-w-2xl text-xl text-gray-400">
          The deployment platform that catches errors before your users do.
          Zero config. Instant rollbacks. Real-time monitoring.
        </p>
        <div className="flex flex-col items-center gap-4 sm:flex-row sm:justify-center">
          <Button size="lg" className="bg-violet-600 text-white hover:bg-violet-500 px-8">
            Start free trial
          </Button>
          <Button size="lg" variant="outline" className="border-gray-700 text-gray-300">
            See how it works →
          </Button>
        </div>
        <p className="mt-4 text-sm text-gray-500">No credit card required · 14-day free trial</p>
      </div>
    </section>
  )
}

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-9 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

SEO Checklist

• <title> tag: primary keyword + brand (50–60 chars)
• Meta description: benefit + CTA (150–160 chars)
• OG image: 1200×630px with product name and tagline
• H1: one per page, includes primary keyword
• Structured data: FAQPage, Product, or Organization schema
• Canonical URL set
• Image alt text on all <Image> components
• robots.txt and sitemap.xml configured
• Core Web Vitals: LCP < 1s, CLS < 0.1
• Mobile viewport meta tag present
• Internal linking to pricing and docs

Validation step: Before outputting final code, verify every checklist item above is satisfied. Fix any gaps inline — do not skip items.

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type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-10 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Common Pitfalls

• Hero image not preloaded — add priority prop to first <Image>
• Missing mobile breakpoints — always design mobile-first with sm: prefixes
• CTA copy too vague — "Get started" beats "Learn more"; "Start free trial" beats "Sign up"
• Pricing page missing trust signals — add money-back guarantee and testimonials near CTA
• No above-the-fold CTA on mobile — ensure button is visible without scrolling on 375px viewport

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type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-11 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

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type: skill lifecycle: stable inheritance: inheritable name: product-analytics description: Use when defining product KPIs, building metric dashboards, running cohort or retention analysis, or interpreting feature adoption trends across product stages. tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Product Analytics

Define, track, and interpret product metrics across discovery, growth, and mature product stages.

When To Use

Use this skill for:

• Metric framework selection (AARRR, North Star, HEART)
• KPI definition by product stage (pre-PMF, growth, mature)
• Dashboard design and metric hierarchy
• Cohort and retention analysis
• Feature adoption and funnel interpretation

Workflow

1. Select metric framework

• AARRR for growth loops and funnel visibility
• North Star for cross-functional strategic alignment
• HEART for UX quality and user experience measurement

2. Define stage-appropriate KPIs

• Pre-PMF: activation, early retention, qualitative success
• Growth: acquisition efficiency, expansion, conversion velocity
• Mature: retention depth, revenue quality, operational efficiency

3. Design dashboard layers

• Executive layer: 5-7 directional metrics
• Product health layer: acquisition, activation, retention, engagement
• Feature layer: adoption, depth, repeat usage, outcome correlation

4. Run cohort + retention analysis

• Segment by signup cohort or feature exposure cohort
• Compare retention curves, not single-point snapshots
• Identify inflection points around onboarding and first value moment

5. Interpret and act

• Connect metric movement to product changes and release timeline
• Distinguish signal from noise using period-over-period context
• Propose one clear product action per major metric risk/opportunity

KPI Guidance By Stage

Pre-PMF

• Activation rate
• Week-1 retention
• Time-to-first-value
• Problem-solution fit interview score

Growth

• Funnel conversion by stage
• Monthly retained users
• Feature adoption among new cohorts
• Expansion / upsell proxy metrics

Mature

• Net revenue retention aligned product metrics
• Power-user share and depth of use
• Churn risk indicators by segment
• Reliability and support-deflection product metrics

Dashboard Design Principles

• Show trends, not isolated point estimates.
• Keep one owner per KPI.
• Pair each KPI with target, threshold, and decision rule.
• Use cohort and segment filters by default.
• Prefer comparable time windows (weekly vs weekly, monthly vs monthly).

See:

• references/metrics-frameworks.md
• references/dashboard-templates.md

Cohort Analysis Method

1. Define cohort anchor event (signup, activation, first purchase).
2. Define retained behavior (active day, key action, repeat session).
3. Build retention matrix by cohort week/month and age period.
4. Compare curve shape across cohorts.
5. Flag early drop points and investigate journey friction.

Retention Curve Interpretation

• Sharp early drop, low plateau: onboarding mismatch or weak initial value.
• Moderate drop, stable plateau: healthy core audience with predictable churn.
• Flattening at low level: product used occasionally, revisit value metric.
• Improving newer cohorts: onboarding or positioning improvements are working.

Anti-Patterns

Anti-pattern	Fix
Vanity metrics — tracking pageviews or total signups without activation context	Always pair acquisition metrics with activation rate and retention
Single-point retention — reporting "30-day retention is 20%"	Compare retention curves across cohorts, not isolated snapshots
Dashboard overload — 30+ metrics on one screen	Executive layer: 5-7 metrics. Feature layer: per-feature only
No decision rule — tracking a KPI with no threshold or action plan	Every KPI needs: target, threshold, owner, and "if below X, then Y"
Averaging across segments — reporting blended metrics that hide segment differences	Always segment by cohort, plan tier, channel, or geography
Ignoring seasonality — comparing this week to last week without adjusting	Use period-over-period with same-period-last-year context

Tooling

scripts/metrics_calculator.py

CLI utility for retention, cohort, and funnel analysis from CSV data. Supports text and JSON output.

# Retention analysis
python3 scripts/metrics_calculator.py retention events.csv
python3 scripts/metrics_calculator.py retention events.csv --format json

# Cohort matrix
python3 scripts/metrics_calculator.py cohort events.csv --cohort-grain month
python3 scripts/metrics_calculator.py cohort events.csv --cohort-grain week --format json

# Funnel conversion
python3 scripts/metrics_calculator.py funnel funnel.csv --stages visit,signup,activate,pay
python3 scripts/metrics_calculator.py funnel funnel.csv --stages visit,signup,activate,pay --format json

CSV format for retention/cohort:

user_id,cohort_date,activity_date
u001,2026-01-01,2026-01-01
u001,2026-01-01,2026-01-03
u002,2026-01-02,2026-01-02

CSV format for funnel:

user_id,stage
u001,visit
u001,signup
u001,activate
u002,visit
u002,signup

Cross-References

• Related: product-team/experiment-designer — for A/B test planning after identifying metric opportunities
• Related: product-team/product-manager-toolkit — for RICE prioritization of metric-driven features
• Related: product-team/product-discovery — for assumption mapping when metrics reveal unknowns
• Related: finance/saas-metrics-coach — for SaaS-specific metrics (ARR, MRR, churn, LTV)

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type: skill lifecycle: stable inheritance: inheritable name: product-discovery description: Use when validating product opportunities, mapping assumptions, planning discovery sprints, or testing problem-solution fit before committing delivery resources. tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Product Discovery

Run structured discovery to identify high-value opportunities and de-risk product bets.

When To Use

Use this skill for:

• Opportunity Solution Tree facilitation
• Assumption mapping and test planning
• Problem validation interviews and evidence synthesis
• Solution validation with prototypes/experiments
• Discovery sprint planning and outputs

Core Discovery Workflow

1. Define desired outcome

• Set one measurable outcome to improve.
• Establish baseline and target horizon.

2. Build Opportunity Solution Tree (OST)

• Outcome -> opportunities -> solution ideas -> experiments
• Keep opportunities grounded in user evidence, not internal opinions.

3. Map assumptions

• Identify desirability, viability, feasibility, and usability assumptions.
• Score assumptions by risk and certainty.

Use:

python3 scripts/assumption_mapper.py assumptions.csv

4. Validate the problem

• Conduct interviews and behavior analysis.
• Confirm frequency, severity, and willingness to solve.
• Reject weak opportunities early.

5. Validate the solution

• Prototype before building.
• Run concept, usability, and value tests.
• Measure behavior, not only stated preference.

6. Plan discovery sprint

• 1-2 week cycle with explicit hypotheses
• Daily evidence reviews
• End with decision: proceed, pivot, or stop

Opportunity Solution Tree (Teresa Torres)

Structure:

• Outcome: metric you want to move
• Opportunities: unmet customer needs/pains
• Solutions: candidate interventions
• Experiments: fastest learning actions

Quality checks:

• At least 3 distinct opportunities before converging.
• At least 2 experiments per top opportunity.
• Tie every branch to evidence source.

Assumption Mapping

Assumption categories:

• Desirability: users want this
• Viability: business value exists
• Feasibility: team can build/operate it
• Usability: users can successfully use it

Prioritization rule:

• High risk + low certainty assumptions are tested first.

Problem Validation Techniques

• Problem interviews focused on current behavior
• Journey friction mapping
• Support ticket and sales-call synthesis
• Behavioral analytics triangulation

Evidence threshold examples:

• Same pain repeated across multiple target users
• Observable workaround behavior
• Measurable cost of current pain

Solution Validation Techniques

• Concept tests (value proposition comprehension)
• Prototype usability tests (task success/time-to-complete)
• Fake door or concierge tests (demand signal)
• Limited beta cohorts (retention/activation signals)

Discovery Sprint Planning

Suggested 10-day structure:

• Day 1-2: Outcome + opportunity framing
• Day 3-4: Assumption mapping + test design
• Day 5-7: Problem and solution tests
• Day 8-9: Evidence synthesis + decision options
• Day 10: Stakeholder decision review

Tooling

scripts/assumption_mapper.py

CLI utility that:

• reads assumptions from CSV or inline input
• scores risk/certainty priority
• emits prioritized test plan with suggested test types

See references/discovery-frameworks.md for framework details.

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type: skill lifecycle: stable inheritance: inheritable name: product-manager-toolkit description: Comprehensive toolkit for product managers including RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, and go-to-market strategies. Use for feature prioritizati... tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Product Manager Toolkit

Essential tools and frameworks for modern product management, from discovery to delivery.

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type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-15 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Quick Start

For Feature Prioritization

# Create sample data file
python scripts/rice_prioritizer.py sample

# Run prioritization with team capacity
python scripts/rice_prioritizer.py sample_features.csv --capacity 15

For Interview Analysis

python scripts/customer_interview_analyzer.py interview_transcript.txt

For PRD Creation

1. Choose template from references/prd_templates.md
2. Fill sections based on discovery work
3. Review with engineering for feasibility
4. Version control in project management tool

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type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-16 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Customer Discovery Process

Plan → Recruit → Interview → Analyze → Synthesize → Validate

Step 1: Plan Research

• Define research questions
• Identify target segments
• Create interview script (see references/frameworks.md)

Step 2: Recruit Participants

• 5-8 interviews per segment
• Mix of power users and churned users
• Incentivize appropriately

Step 3: Conduct Interviews

• Use semi-structured format
• Focus on problems, not solutions
• Record with permission
• Take minimal notes during interview

Step 4: Analyze Insights

python scripts/customer_interview_analyzer.py transcript.txt

Extracts:

• Pain points with severity
• Feature requests with priority
• Jobs to be done patterns
• Sentiment and key themes
• Notable quotes

Step 5: Synthesize Findings

• Group similar pain points across interviews
• Identify patterns (3+ mentions = pattern)
• Map to opportunity areas using Opportunity Solution Tree
• Prioritize opportunities by frequency and severity

Step 6: Validate Solutions

Before building:

• Create solution hypotheses (see references/frameworks.md)
• Test with low-fidelity prototypes
• Measure actual behavior vs stated preference
• Iterate based on feedback
• Document learnings for future research

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-17 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Tools Reference

RICE Prioritizer

Advanced RICE framework implementation with portfolio analysis.

Features:

• RICE score calculation with configurable weights
• Portfolio balance analysis (quick wins vs big bets)
• Quarterly roadmap generation based on capacity
• Multiple output formats (text, JSON, CSV)

CSV Input Format:

name,reach,impact,confidence,effort,description
User Dashboard Redesign,5000,high,high,l,Complete redesign
Mobile Push Notifications,10000,massive,medium,m,Add push support
Dark Mode,8000,medium,high,s,Dark theme option

Commands:

# Create sample data
python scripts/rice_prioritizer.py sample

# Run with default capacity (10 person-months)
python scripts/rice_prioritizer.py features.csv

# Custom capacity
python scripts/rice_prioritizer.py features.csv --capacity 20

# JSON output for integration
python scripts/rice_prioritizer.py features.csv --output json

# CSV output for spreadsheets
python scripts/rice_prioritizer.py features.csv --output csv

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-18 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Input/Output Examples

→ See references/input-output-examples.md for details

Integration Points

Compatible tools and platforms:

Category	Platforms
Analytics	Amplitude, Mixpanel, Google Analytics
Roadmapping	ProductBoard, Aha!, Roadmunk, Productplan
Design	Figma, Sketch, Miro
Development	Jira, Linear, GitHub, Asana
Research	Dovetail, UserVoice, Pendo, Maze
Communication	Slack, Notion, Confluence

JSON export enables integration with most tools:

# Export for Jira import
python scripts/rice_prioritizer.py features.csv --output json > priorities.json

# Export for dashboard
python scripts/customer_interview_analyzer.py interview.txt json > insights.json

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-19 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Best Practices

Writing Great PRDs:

• Start with the problem, not the solution
• Include clear success metrics upfront
• Explicitly state what's out of scope
• Use visuals (wireframes, flows, diagrams)
• Keep technical details in appendix
• Version control all changes

Effective Prioritization:

• Mix quick wins with strategic bets
• Consider opportunity cost of delays
• Account for dependencies between features
• Buffer 20% for unexpected work
• Revisit priorities quarterly
• Communicate decisions with context

Customer Discovery:

• Ask "why" five times to find root cause
• Focus on past behavior, not future intentions
• Avoid leading questions ("Wouldn't you love...")
• Interview in the user's natural environment
• Watch for emotional reactions (pain = opportunity)
• Validate qualitative with quantitative data

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-20 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Reference Documents

• references/prd_templates.md - PRD templates for different contexts
• references/frameworks.md - Detailed framework documentation (RICE, MoSCoW, Kano, JTBD, etc.)

---

type: skill lifecycle: stable inheritance: inheritable name: product-skills description: 10 product agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. PM toolkit (RICE), agile PO, product strategist (OKR), UX researcher, UI design system, competitive teardow... tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Product Team Skills

8 production-ready product skills covering product management, UX/UI design, and SaaS development.

Quick Start

Claude Code

/read product-team/product-manager-toolkit/SKILL.md

Codex CLI

npx agent-skills-cli add alirezarezvani/claude-skills/product-team

Skills Overview

Skill	Folder	Focus
Product Manager Toolkit	product-manager-toolkit/	RICE prioritization, customer discovery, PRDs
Agile Product Owner	agile-product-owner/	User stories, sprint planning, backlog
Product Strategist	product-strategist/	OKR cascades, market analysis, vision
UX Researcher Designer	ux-researcher-designer/	Personas, journey maps, usability testing
UI Design System	ui-design-system/	Design tokens, component docs, responsive
Competitive Teardown	competitive-teardown/	Systematic competitor analysis
Landing Page Generator	landing-page-generator/	Conversion-optimized pages
SaaS Scaffolder	saas-scaffolder/	Production SaaS boilerplate

Python Tools

9 scripts, all stdlib-only:

python3 product-manager-toolkit/scripts/rice_prioritizer.py --help
python3 product-strategist/scripts/okr_cascade_generator.py --help

Rules

• Load only the specific skill SKILL.md you need
• Use Python tools for scoring and analysis, not manual judgment

---

type: skill lifecycle: stable inheritance: inheritable name: product-strategist description: Strategic product leadership toolkit for Head of Product covering OKR cascade generation, quarterly planning, competitive landscape analysis, product vision documents, and team scaling proposals. U... tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Product Strategist

Strategic toolkit for Head of Product to drive vision, alignment, and organizational excellence.

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-23 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Quick Start

# Growth strategy with default teams
python scripts/okr_cascade_generator.py growth

# Retention strategy with custom teams
python scripts/okr_cascade_generator.py retention --teams "Engineering,Design,Data"

# Revenue strategy with 40% product contribution
python scripts/okr_cascade_generator.py revenue --contribution 0.4

# Export as JSON for integration
python scripts/okr_cascade_generator.py growth --json > okrs.json

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-24 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

OKR Cascade Generator

Usage

python scripts/okr_cascade_generator.py [strategy] [options]

Strategies: growth | retention | revenue | innovation | operational

Configuration Options

Option	Description	Default
--teams, -t	Comma-separated team names	Growth,Platform,Mobile,Data
--contribution, -c	Product contribution to company OKRs (0-1)	0.3 (30%)
--json, -j	Output as JSON instead of dashboard	False
--metrics, -m	Metrics as JSON string	Sample metrics

Output Examples

Dashboard Output (growth strategy)

============================================================
OKR CASCADE DASHBOARD
Quarter: Q1 2025  |  Strategy: GROWTH
Teams: Growth, Platform, Mobile, Data  |  Product Contribution: 30%
============================================================

🏢 COMPANY OKRS
📌 CO-1: Accelerate user acquisition and market expansion
   └─ CO-1-KR1: Increase MAU from 100,000 to 150,000
   └─ CO-1-KR2: Achieve 50% MoM growth rate
   └─ CO-1-KR3: Expand to 3 new markets

📌 CO-2: Achieve product-market fit in new segments
📌 CO-3: Build sustainable growth engine

🚀 PRODUCT OKRS
📌 PO-1: Build viral product features and market expansion
   ↳ Supports: CO-1
   └─ PO-1-KR1: Increase product MAU to 45,000
   └─ PO-1-KR2: Achieve 45% feature adoption rate

👥 TEAM OKRS
Growth Team:
  📌 GRO-1: Build viral product features through acquisition and activation
     └─ GRO-1-KR1: Increase product MAU to 11,250
     └─ GRO-1-KR2: Achieve 11.25% feature adoption rate

🎯 ALIGNMENT SCORES
✓ Vertical Alignment: 100.0%
! Horizontal Alignment: 75.0%
✓ Coverage: 100.0%  |  ✓ Balance: 97.5%  |  ✓ Overall: 94.0%
✅ Overall alignment is GOOD (≥80%)

JSON Output (retention --json, truncated)

{
  "quarter": "Q1 2025",
  "strategy": "retention",
  "company": {
    "objectives": [
      {
        "id": "CO-1",
        "title": "Create lasting customer value and loyalty",
        "key_results": [
          { "id": "CO-1-KR1", "title": "Improve retention from 70% to 85%", "current": 70, "target": 85 }
        ]
      }
    ]
  },
  "product": { "contribution": 0.3, "objectives": ["..."] },
  "teams": ["..."],
  "alignment_scores": {
    "vertical_alignment": 100.0, "horizontal_alignment": 75.0,
    "coverage": 100.0, "balance": 97.5, "overall": 94.0
  }
}

See references/examples/sample_growth_okrs.json for a complete example.

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-25 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Best Practices

OKR Cascade

• Limit to 3-5 objectives per level, each with 3-5 key results
• Key results must be measurable with current and target values
• Validate parent-child relationships before finalizing

Alignment Scoring

• Target >80% overall alignment; investigate any score below 60%
• Balance scores ensure no team is overloaded
• Horizontal alignment prevents conflicting goals across teams

Team Configuration

• Configure teams to match your actual org structure
• Adjust contribution percentages based on team size
• Platform/Infrastructure teams often support all objectives
• Specialized teams (ML, Data) may only support relevant objectives

Related Skills

• Senior PM (project-management/senior-pm/) — Portfolio management and risk analysis inform strategic planning
• Competitive Teardown (product-team/competitive-teardown/) — Competitive intelligence feeds product strategy

---

type: skill lifecycle: stable inheritance: inheritable name: roadmap-communicator description: Use when preparing roadmap narratives, release notes, changelogs, or stakeholder updates tailored for executives, engineering teams, and customers. tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Roadmap Communicator

Create clear roadmap communication artifacts for internal and external stakeholders.

When To Use

Use this skill for:

• Building roadmap presentations in different formats
• Writing stakeholder updates (board, engineering, customers)
• Producing release notes (user-facing and internal)
• Generating changelogs from git history
• Structuring feature announcements

Roadmap Formats

1. Now / Next / Later

• Best for uncertainty and strategic flexibility.
• Communicate direction without false precision.

2. Timeline roadmap

• Best for fixed-date commitments and launch coordination.
• Requires active risk and dependency management.

3. Theme-based roadmap

• Best for outcome-led planning and cross-team alignment.
• Groups initiatives by problem space or strategic objective.

See references/roadmap-templates.md for templates.

Stakeholder Update Patterns

Board / Executive

• Outcome and risk oriented
• Focus on progress against strategic goals
• Highlight trade-offs and required decisions

Engineering

• Scope, dependencies, and sequencing clarity
• Status, blockers, and resourcing implications

Customers

• Value narrative and timing window
• What is available now vs upcoming
• Clear expectation setting

See references/communication-templates.md for reusable templates.

Release Notes Guidance

User-Facing Release Notes

• Lead with user value, not internal implementation details.
• Group by workflows or user jobs.
• Include migration/behavior changes explicitly.

Internal Release Notes

• Include technical details, operational impact, and known issues.
• Capture rollout plan, rollback criteria, and monitoring notes.

Changelog Generation

Use:

python3 scripts/changelog_generator.py --from v1.0.0 --to HEAD

Features:

• Reads git log range
• Parses conventional commit prefixes
• Groups entries by type (feat, fix, chore, etc.)
• Outputs markdown or plain text

Feature Announcement Framework

1. Problem context
2. What changed
3. Why it matters
4. Who benefits most
5. How to get started
6. Call to action and feedback channel

Communication Quality Checklist

• Audience-specific framing is explicit.
• Outcomes and trade-offs are clear.
• Terminology is consistent across artifacts.
• Risks and dependencies are not hidden.
• Next actions and owners are specified.

---

type: skill lifecycle: stable inheritance: inheritable name: saas-scaffolder description: Generates complete, production-ready SaaS project boilerplate including authentication, database schemas, billing integration, API routes, and a working dashboard using Next.js 14+ App Router, Type... tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

SaaS Scaffolder

Tier: POWERFUL
Category: Product Team
Domain: Full-Stack Development / Project Bootstrapping

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-28 description: [1-3 sentences] tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

File Tree Output

my-saas/
├── app/
│   ├── (auth)/
│   │   ├── login/page.tsx
│   │   ├── register/page.tsx
│   │   └── layout.tsx
│   ├── (dashboard)/
│   │   ├── dashboard/page.tsx
│   │   ├── settings/page.tsx
│   │   ├── billing/page.tsx
│   │   └── layout.tsx
│   ├── (marketing)/
│   │   ├── page.tsx
│   │   ├── pricing/page.tsx
│   │   └── layout.tsx
│   ├── api/
│   │   ├── auth/[...nextauth]/route.ts
│   │   ├── webhooks/stripe/route.ts
│   │   ├── billing/checkout/route.ts
│   │   └── billing/portal/route.ts
│   └── layout.tsx
├── components/
│   ├── ui/
│   ├── auth/
│   │   ├── login-form.tsx
│   │   └── register-form.tsx
│   ├── dashboard/
│   │   ├── sidebar.tsx
│   │   ├── header.tsx
│   │   └── stats-card.tsx
│   ├── marketing/
│   │   ├── hero.tsx
│   │   ├── features.tsx
│   │   ├── pricing.tsx
│   │   └── footer.tsx
│   └── billing/
│       ├── plan-card.tsx
│       └── usage-meter.tsx
├── lib/
│   ├── auth.ts
│   ├── db.ts
│   ├── stripe.ts
│   ├── validations.ts
│   └── utils.ts
├── db/
│   ├── schema.ts
│   └── migrations/
├── hooks/
│   ├── use-subscription.ts
│   └── use-user.ts
├── types/index.ts
├── middleware.ts
├── .env.example
├── drizzle.config.ts
└── next.config.ts

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-29 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Scaffold Checklist

The following phases must be completed in order. Validate at the end of each phase before proceeding.

Phase 1 — Foundation

• 1. Next.js initialized with TypeScript and App Router
• 2. Tailwind CSS configured with custom theme tokens
• 3. shadcn/ui installed and configured
• 4. ESLint + Prettier configured
• 5. .env.example created with all required variables

✅ Validate: Run npm run build — no TypeScript or lint errors should appear.
🔧 If build fails: Check tsconfig.json paths and that all shadcn/ui peer dependencies are installed.

Phase 2 — Database

• 6. Drizzle ORM installed and configured
• 7. Schema written (users, accounts, sessions, verification_tokens)
• 8. Initial migration generated and applied
• 9. DB client singleton exported from lib/db.ts
• 10. DB connection tested in local environment

✅ Validate: Run a simple db.select().from(users) in a test script — it should return an empty array without throwing.
🔧 If DB connection fails: Verify DATABASE_URL format includes ?sslmode=require for NeonDB/Supabase. Check that the migration has been applied with drizzle-kit push (dev) or drizzle-kit migrate (prod).

Phase 3 — Authentication

• 11. Auth provider installed (NextAuth / Clerk / Supabase)
• 12. OAuth provider configured (Google / GitHub)
• 13. Auth API route created
• 14. Session callback adds user ID and subscription status
• 15. Middleware protects dashboard routes
• 16. Login and register pages built with error states

✅ Validate: Sign in via OAuth, confirm session user has id and subscriptionStatus. Attempt to access /dashboard without a session — you should be redirected to /login.
🔧 If sign-out loops occur in production: Ensure NEXTAUTH_SECRET is set and consistent across deployments. Add declare module "next-auth" to extend session types if TypeScript errors appear.

Phase 4 — Payments

• 17. Stripe client initialized with TypeScript types
• 18. Checkout session route created
• 19. Customer portal route created
• 20. Stripe webhook handler with signature verification
• 21. Webhook updates user subscription status in DB idempotently

✅ Validate: Complete a Stripe test checkout using a 4242 4242 4242 4242 card. Confirm stripeSubscriptionId is written to the DB. Replay the checkout.session.completed webhook event and confirm idempotency (no duplicate DB writes).
🔧 If webhook signature fails: Use stripe listen --forward-to localhost:3000/api/webhooks/stripe locally — never hardcode the raw webhook secret. Verify STRIPE_WEBHOOK_SECRET matches the listener output.

Phase 5 — UI

• 22. Landing page with hero, features, pricing sections
• 23. Dashboard layout with sidebar and responsive header
• 24. Billing page showing current plan and upgrade options
• 25. Settings page with profile update form and success states

✅ Validate: Run npm run build for a final production build check. Navigate all routes manually and confirm no broken layouts, missing session data, or hydration errors.

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-30 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

---

type: skill lifecycle: stable inheritance: inheritable name: spec-to-repo description: Use when the user says 'build me an app', 'create a project from this spec', 'scaffold a new repo', 'generate a starter', 'turn this idea into code', 'bootstrap a project', 'I have requirements and... tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Spec to Repo

Turn a natural-language project specification into a complete, runnable starter repository. Not a template filler — a spec interpreter that generates real, working code for any stack.

When to Use

• User provides a text description of an app and wants code
• User has a PRD, requirements doc, or feature list and needs a codebase
• User says "build me an app that...", "scaffold this", "bootstrap a project"
• User wants a working starter repo, not just a file tree

Not this skill when the user wants a SaaS app with Stripe + Auth specifically — use product-team/saas-scaffolder instead.

Core Workflow

Phase 1 — Parse & Interpret

Read the spec. Extract these fields silently:

Field	Source	Required
App name	Explicit or infer from description	yes
Description	First sentence of spec	yes
Features	Bullet points or sentences describing behavior	yes
Tech stack	Explicit ("use FastAPI") or infer from context	yes
Auth	"login", "users", "accounts", "roles"	if mentioned
Database	"store", "save", "persist", "records", "schema"	if mentioned
API surface	"endpoint", "API", "REST", "GraphQL"	if mentioned
Deploy target	"Vercel", "Docker", "AWS", "Railway"	if mentioned

Stack inference rules (when user doesn't specify):

Signal	Inferred stack
"web app", "dashboard", "SaaS"	Next.js + TypeScript
"API", "backend", "microservice"	FastAPI (Python) or Express (Node)
"mobile app"	Flutter or React Native
"CLI tool"	Go or Python
"data pipeline"	Python
"high performance", "systems"	Rust or Go

After parsing, present a structured interpretation back to the user:

## Spec Interpretation

**App:** [name]
**Stack:** [framework + language]
**Features:**
1. [feature]
2. [feature]

**Database:** [yes/no — engine]
**Auth:** [yes/no — method]
**Deploy:** [target]

Does this match your intent? Any corrections before I generate?

Flag ambiguities. Ask at most 3 clarifying questions. If the user says "just build it", proceed with best-guess defaults.

Phase 2 — Architecture

Design the project before writing any files:

1. Select template — Match to a stack template from references/stack-templates.md
2. Define file tree — List every file that will be created
3. Map features to files — Each feature gets at minimum one file/component
4. Design database schema — If applicable, define tables/collections with fields and types
5. Identify dependencies — List every package with version constraints
6. Plan API routes — If applicable, list every endpoint with method, path, request/response shape

Present the file tree to the user before generating:

project-name/
├── README.md
├── .env.example
├── .gitignore
├── .github/workflows/ci.yml
├── package.json / requirements.txt / go.mod
├── src/
│   ├── ...
├── tests/
│   ├── ...
└── ...

Phase 3 — Generate

Write every file. Rules:

• Real code, not stubs. Every function has a real implementation. No // TODO: implement or pass placeholders.
• Syntactically valid. Every file must parse without errors in its language.
• Imports match dependencies. Every import must correspond to a package in the manifest (package.json, requirements.txt, go.mod, etc.).
• Types included. TypeScript projects use types. Python projects use type hints. Go projects use typed structs.
• Environment variables. Generate .env.example with every required variable, commented with purpose.
• README.md. Include: project description, prerequisites, setup steps (clone, install, configure env, run), and available scripts/commands.
• CI config. Generate .github/workflows/ci.yml with: install, lint (if linter in deps), test, build.
• .gitignore. Stack-appropriate ignores (node_modules, pycache, .env, build artifacts).

File generation order:

1. Manifest (package.json / requirements.txt / go.mod)
2. Config files (.env.example, .gitignore, CI)
3. Database schema / migrations
4. Core business logic
5. API routes / endpoints
6. UI components (if applicable)
7. Tests
8. README.md

Phase 4 — Validate

After generation, run through this checklist:

• Every imported package exists in the manifest
• Every file referenced by an import exists in the tree
• .env.example lists every env var used in code
• .gitignore covers build artifacts and secrets
• README has setup instructions that actually work
• No hardcoded secrets, API keys, or passwords
• At least one test file exists
• Build/start command is documented and would work

Run scripts/validate_project.py against the generated directory to catch common issues.

Examples

Example 1: Task Management API

Input spec:

"Build me a task management API. Users can create, list, update, and delete tasks. Tasks have a title, description, status (todo/in-progress/done), and due date. Use FastAPI with SQLite. Add basic auth with API keys."

Output file tree:

task-api/
├── README.md
├── .env.example              # API_KEY, DATABASE_URL
├── .gitignore
├── .github/workflows/ci.yml
├── requirements.txt          # fastapi, uvicorn, sqlalchemy, pytest
├── main.py                   # FastAPI app, CORS, lifespan
├── models.py                 # SQLAlchemy Task model
├── schemas.py                # Pydantic request/response schemas
├── database.py               # SQLite engine + session
├── auth.py                   # API key middleware
├── routers/
│   └── tasks.py              # CRUD endpoints
└── tests/
    └── test_tasks.py         # Smoke tests for each endpoint

Example 2: Recipe Sharing Web App

Input spec:

"I want a recipe sharing website. Users sign up, post recipes with ingredients and steps, browse other recipes, and save favorites. Use Next.js with Tailwind. Store data in PostgreSQL."

Output file tree:

recipe-share/
├── README.md
├── .env.example              # DATABASE_URL, NEXTAUTH_SECRET, NEXTAUTH_URL
├── .gitignore
├── .github/workflows/ci.yml
├── package.json              # next, react, tailwindcss, prisma, next-auth
├── tailwind.config.ts
├── tsconfig.json
├── next.config.ts
├── prisma/
│   └── schema.prisma         # User, Recipe, Ingredient, Favorite models
├── src/
│   ├── app/
│   │   ├── layout.tsx
│   │   ├── page.tsx          # Homepage — recipe feed
│   │   ├── recipes/
│   │   │   ├── page.tsx      # Browse recipes
│   │   │   ├── [id]/page.tsx # Recipe detail
│   │   │   └── new/page.tsx  # Create recipe form
│   │   └── api/
│   │       ├── auth/[...nextauth]/route.ts
│   │       └── recipes/route.ts
│   ├── components/
│   │   ├── RecipeCard.tsx
│   │   ├── RecipeForm.tsx
│   │   └── Navbar.tsx
│   └── lib/
│       ├── prisma.ts
│       └── auth.ts
└── tests/
    └── recipes.test.ts

Example 3: CLI Expense Tracker

Input spec:

"Python CLI tool for tracking expenses. Commands: add, list, summary, export-csv. Store in a local SQLite file. No external API."

Output file tree:

expense-tracker/
├── README.md
├── .gitignore
├── .github/workflows/ci.yml
├── pyproject.toml
├── src/
│   └── expense_tracker/
│       ├── __init__.py
│       ├── cli.py            # argparse commands
│       ├── database.py       # SQLite operations
│       ├── models.py         # Expense dataclass
│       └── formatters.py     # Table + CSV output
└── tests/
    └── test_cli.py

Anti-Patterns

Anti-pattern	Fix
Placeholder code — // TODO: implement, pass, empty function bodies	Every function has a real implementation. If complex, implement a working simplified version.
Stack override — picking Next.js when the user said Flask	Always honor explicit tech preferences. Only infer when the user doesn't specify.
Missing .gitignore — committing node_modules or .env	Generate stack-appropriate .gitignore as one of the first files.
Phantom imports — importing packages not in the manifest	Cross-check every import against package.json / requirements.txt before finishing.
Over-engineering MVP — adding Redis caching, rate limiting, WebSockets to a v1	Build the minimum that works. The user can iterate.
Ignoring stated preferences — user says "PostgreSQL" and you generate MongoDB	Parse the spec carefully. Explicit preferences are non-negotiable.
Missing env vars — code reads process.env.X but .env.example doesn't list it	Every env var used in code must appear in .env.example with a comment.
No tests — shipping a repo with zero test files	At minimum: one smoke test per API endpoint or one test per core function.
Hallucinated APIs — generating code that calls library methods that don't exist	Stick to well-documented, stable APIs. When unsure, use the simplest approach.

Validation Script

scripts/validate_project.py

Checks a generated project directory for common issues:

# Validate a generated project
python3 scripts/validate_project.py /path/to/generated-project

# JSON output
python3 scripts/validate_project.py /path/to/generated-project --format json

Checks performed:

• README.md exists and is non-empty
• .gitignore exists
• .env.example exists (if code references env vars)
• Package manifest exists (package.json, requirements.txt, go.mod, Cargo.toml, pubspec.yaml)
• No .env file committed (secrets leak)
• At least one test file exists
• No TODO/FIXME placeholders in generated code

Progressive Enhancement

For complex specs, generate in stages:

1. MVP — Core feature only, working end-to-end
2. Auth — Add authentication if requested
3. Polish — Error handling, validation, loading states
4. Deploy — Docker, CI, deploy config

Ask the user after MVP: "Core is working. Want me to add auth/polish/deploy next, or iterate on what's here?"

Cross-References

• Related: product-team/saas-scaffolder — SaaS-specific scaffolding (Next.js + Stripe + Auth)
• Related: engineering/spec-driven-workflow — spec-first development methodology
• Related: engineering/database-designer — database schema design patterns
• Related: engineering-team/senior-fullstack — full-stack implementation patterns

---

type: skill lifecycle: stable inheritance: inheritable name: ui-design-system description: UI design system toolkit for Senior UI Designer including design token generation, component documentation, responsive design calculations, and developer handoff tools. Use for creating design syst... tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

UI Design System

Generate design tokens, create color palettes, calculate typography scales, build component systems, and prepare developer handoff documentation.

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-33 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Trigger Terms

Use this skill when you need to:

• "generate design tokens"
• "create color palette"
• "build typography scale"
• "calculate spacing system"
• "create design system"
• "generate CSS variables"
• "export SCSS tokens"
• "set up component architecture"
• "document component library"
• "calculate responsive breakpoints"
• "prepare developer handoff"
• "convert brand color to palette"
• "check WCAG contrast"
• "build 8pt grid system"

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-34 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Workflow 2: Create Component System

Situation: You need to structure a component library using design tokens.

Steps:

1. Define component hierarchy

   • Atoms: Button, Input, Icon, Label, Badge
   • Molecules: FormField, SearchBar, Card, ListItem
   • Organisms: Header, Footer, DataTable, Modal
   • Templates: DashboardLayout, AuthLayout

2. Map tokens to components

   Component	Tokens Used
   Button	colors, sizing, borders, shadows, typography
   Input	colors, sizing, borders, spacing
   Card	colors, borders, shadows, spacing
   Modal	colors, shadows, spacing, z-index, animation

3. Define variant patterns

   Size variants:

   sm: height 32px, paddingX 12px, fontSize 14px
   md: height 40px, paddingX 16px, fontSize 16px
   lg: height 48px, paddingX 20px, fontSize 18px
   

   Color variants:

   primary: background primary-500, text white
   secondary: background neutral-100, text neutral-900
   ghost: background transparent, text neutral-700
   

4. Document component API

   • Props interface with types
   • Variant options
   • State handling (hover, active, focus, disabled)
   • Accessibility requirements

5. Reference: See references/component-architecture.md

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-35 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Workflow 4: Developer Handoff

Situation: You need to hand off design tokens to development team.

Steps:

1. Export tokens in required formats

   # For CSS projects
   python scripts/design_token_generator.py "#0066CC" modern css
   
   # For SCSS projects
   python scripts/design_token_generator.py "#0066CC" modern scss
   
   # For JavaScript/TypeScript
   python scripts/design_token_generator.py "#0066CC" modern json
   

2. Prepare framework integration

   React + CSS Variables:

   import './design-tokens.css';
   
   <button className="btn btn-primary">Click</button>
   

   Tailwind Config:

   const tokens = require('./design-tokens.json');
   
   module.exports = {
     theme: {
       colors: tokens.colors,
       fontFamily: tokens.typography.fontFamily
     }
   };
   

   styled-components:

   import tokens from './design-tokens.json';
   
   const Button = styled.button`
     background: ${tokens.colors.primary['500']};
     padding: ${tokens.spacing['2']} ${tokens.spacing['4']};
   `;
   

3. Sync with Figma

   • Install Tokens Studio plugin
   • Import design-tokens.json
   • Tokens sync automatically with Figma styles

4. Handoff checklist

   • Token files added to project
   • Build pipeline configured
   • Theme/CSS variables imported
   • Component library aligned
   • Documentation generated

5. Reference: See references/developer-handoff.md

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-36 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Quick Reference Tables

Color Scale Generation

Step	Brightness	Saturation	Use Case
50	95% fixed	30%	Subtle backgrounds
100	95% fixed	38%	Light backgrounds
200	95% fixed	46%	Hover states
300	95% fixed	54%	Borders
400	95% fixed	62%	Disabled states
500	Original	70%	Base/default color
600	Original × 0.8	78%	Hover (dark)
700	Original × 0.6	86%	Active states
800	Original × 0.4	94%	Text
900	Original × 0.2	100%	Headings

Typography Scale (1.25x Ratio)

Size	Value	Calculation
xs	10px	16 ÷ 1.25²
sm	13px	16 ÷ 1.25¹
base	16px	Base
lg	20px	16 × 1.25¹
xl	25px	16 × 1.25²
2xl	31px	16 × 1.25³
3xl	39px	16 × 1.25⁴
4xl	49px	16 × 1.25⁵
5xl	61px	16 × 1.25⁶

WCAG Contrast Requirements

Level	Normal Text	Large Text
AA	4.5:1	3:1
AAA	7:1	4.5:1

Large text: ≥18pt regular or ≥14pt bold

Style Presets

Aspect	Modern	Classic	Playful
Font Sans	Inter	Helvetica	Poppins
Font Mono	Fira Code	Courier	Source Code Pro
Radius Default	8px	4px	16px
Shadows	Layered, subtle	Single layer	Soft, pronounced

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-37 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Validation Checklist

Token Generation

• Brand color provided in hex format
• Style matches project requirements
• All token categories generated
• Semantic colors include contrast values

Component System

• All sizes implemented (sm, md, lg)
• All variants implemented (primary, secondary, ghost)
• All states working (hover, active, focus, disabled)
• Uses only design tokens (no hardcoded values)

Accessibility

• Color contrast meets WCAG AA
• Focus indicators visible
• Touch targets ≥ 44×44px
• Semantic HTML elements used

Developer Handoff

• Tokens exported in required format
• Framework integration documented
• Design tool synced
• Component documentation complete

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type: skill lifecycle: stable inheritance: inheritable name: ux-researcher-designer description: UX research and design toolkit for Senior UX Designer/Researcher including data-driven persona generation, journey mapping, usability testing frameworks, and research synthesis. Use for user resear... tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

UX Researcher & Designer

Generate user personas from research data, create journey maps, plan usability tests, and synthesize research findings into actionable design recommendations.

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type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-39 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Trigger Terms

Use this skill when you need to:

• "create user persona"
• "generate persona from data"
• "build customer journey map"
• "map user journey"
• "plan usability test"
• "design usability study"
• "analyze user research"
• "synthesize interview findings"
• "identify user pain points"
• "define user archetypes"
• "calculate research sample size"
• "create empathy map"
• "identify user needs"

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-40 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Workflow 2: Create Journey Map

Situation: You need to visualize the end-to-end user experience for a specific goal.

Steps:

1. Define scope

   Element	Description
   Persona	Which user type
   Goal	What they're trying to achieve
   Start	Trigger that begins journey
   End	Success criteria
   Timeframe	Hours/days/weeks

2. Gather journey data

   Sources:

   • User interviews (ask "walk me through...")
   • Session recordings
   • Analytics (funnel, drop-offs)
   • Support tickets

3. Map the stages

   Typical B2B SaaS stages:

   Awareness → Evaluation → Onboarding → Adoption → Advocacy
   

4. Fill in layers for each stage

   Stage: [Name]
   ├── Actions: What does user do?
   ├── Touchpoints: Where do they interact?
   ├── Emotions: How do they feel? (1-5)
   ├── Pain Points: What frustrates them?
   └── Opportunities: Where can we improve?
   

5. Identify opportunities

   Priority Score = Frequency × Severity × Solvability

6. Reference: See references/journey-mapping-guide.md for templates

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-41 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Workflow 4: Synthesize Research

Situation: You have raw research data (interviews, surveys, observations) and need actionable insights.

Steps:

1. Code the data

   Tag each data point:

   • [GOAL] - What they want to achieve
   • [PAIN] - What frustrates them
   • [BEHAVIOR] - What they actually do
   • [CONTEXT] - When/where they use product
   • [QUOTE] - Direct user words

2. Cluster similar patterns

   User A: Uses daily, advanced features, shortcuts
   User B: Uses daily, complex workflows, automation
   User C: Uses weekly, basic needs, occasional
   
   Cluster 1: A, B (Power Users)
   Cluster 2: C (Casual User)
   

3. Calculate segment sizes

   Cluster	Users	%	Viability
   Power Users	18	36%	Primary persona
   Business Users	15	30%	Primary persona
   Casual Users	12	24%	Secondary persona

4. Extract key findings

   For each theme:

   • Finding statement
   • Supporting evidence (quotes, data)
   • Frequency (X/Y participants)
   • Business impact
   • Recommendation

5. Prioritize opportunities

   Factor	Score 1-5
   Frequency	How often does this occur?
   Severity	How much does it hurt?
   Breadth	How many users affected?
   Solvability	Can we fix this?

6. Reference: See references/persona-methodology.md for analysis framework

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-42 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Quick Reference Tables

Research Method Selection

Question Type	Best Method	Sample Size
"What do users do?"	Analytics, observation	100+ events
"Why do they do it?"	Interviews	8-15 users
"How well can they do it?"	Usability test	5-8 users
"What do they prefer?"	Survey, A/B test	50+ users
"What do they feel?"	Diary study, interviews	10-15 users

Persona Confidence Levels

Sample Size	Confidence	Use Case
5-10 users	Low	Exploratory
11-30 users	Medium	Directional
31+ users	High	Production

Usability Issue Severity

Severity	Definition	Action
4 - Critical	Prevents task completion	Fix immediately
3 - Major	Significant difficulty	Fix before release
2 - Minor	Causes hesitation	Fix when possible
1 - Cosmetic	Noticed but not problematic	Low priority

Interview Question Types

Type	Example	Use For
Context	"Walk me through your typical day"	Understanding environment
Behavior	"Show me how you do X"	Observing actual actions
Goals	"What are you trying to achieve?"	Uncovering motivations
Pain	"What's the hardest part?"	Identifying frustrations
Reflection	"What would you change?"	Generating ideas

---

type: skill lifecycle: stable inheritance: inheritable name: product-team-skill-43 description: Skill from product-team plugin tier: standard applyTo: '/product,/ux,/roadmap,/discovery' currency: 2026-05-03 lastReviewed: 2026-05-03

Validation Checklist

Persona Quality

• Based on 20+ users (minimum)
• At least 2 data sources (quant + qual)
• Specific, actionable goals
• Frustrations include frequency counts
• Design implications are specific
• Confidence level stated

Journey Map Quality

• Scope clearly defined (persona, goal, timeframe)
• Based on real user data, not assumptions
• All layers filled (actions, touchpoints, emotions)
• Pain points identified per stage
• Opportunities prioritized

Usability Test Quality

• Research questions are testable
• Tasks are realistic scenarios, not instructions
• 5+ participants per design
• Success metrics defined
• Findings include severity ratings

Research Synthesis Quality

• Data coded consistently
• Patterns based on 3+ data points
• Findings include evidence
• Recommendations are actionable
• Priorities justified

Related Skills

• UI Design System (product-team/ui-design-system/) — Research findings inform design system decisions
• Product Manager Toolkit (product-team/product-manager-toolkit/) — Customer interview analysis complements persona research