c-level-advisor/skills/cpo-advisor/SKILL.md
Product leadership for scaling companies. Product vision, portfolio strategy, product-market fit, and product org design. Use when setting product vision, managing a product portfolio, measuring PMF, designing product teams, prioritizing at the portfolio level, reporting to the board on product, or when user mentions CPO, product strategy, product-market fit, product organization, portfolio prioritization, or roadmap strategy.
npx skillsauth add alirezarezvani/claude-skills cpo-advisorInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Strategic product leadership. Vision, portfolio, PMF, org design. Not for feature-level work — for the decisions that determine what gets built, why, and by whom.
CPO, chief product officer, product strategy, product vision, product-market fit, PMF, portfolio management, product org, roadmap strategy, product metrics, north star metric, retention curve, product trio, team topologies, Jobs to be Done, category design, product positioning, board product reporting, invest-maintain-kill, BCG matrix, switching costs, network effects
python scripts/pmf_scorer.py
Multi-dimensional PMF score across retention, engagement, satisfaction, and growth.
python scripts/portfolio_analyzer.py
BCG matrix classification, investment recommendations, portfolio health score.
The CPO owns three things. Everything else is delegation.
| Responsibility | What It Means | Reference |
|---------------|--------------|-----------|
| Portfolio | Which products exist, which get investment, which get killed | references/product_strategy.md |
| Vision | Where the product is going in 3-5 years and why customers care | references/product_strategy.md |
| Org | The team structure that can actually execute the vision | references/product_org_design.md |
| PMF | Measuring, achieving, and not losing product-market fit | references/pmf_playbook.md |
| Metrics | North star → leading → lagging hierarchy, board reporting | This file |
These questions expose whether you have a strategy or a list.
Portfolio:
PMF:
Org:
Strategy:
North Star Metric (1, owned by CPO)
↓ explains changes in
Leading Indicators (3-5, owned by PMs)
↓ eventually become
Lagging Indicators (revenue, churn, NPS)
North Star rules: One number. Measures customer value delivered, not revenue. Every team can influence it.
Good North Stars by business model:
| Model | North Star Example | |-------|------------------| | B2B SaaS | Weekly active accounts using core feature | | Consumer | D30 retained users | | Marketplace | Successful transactions per week | | PLG | Accounts reaching "aha moment" within 14 days | | Data product | Queries run per active user per week |
| Category | Metric | Frequency | |----------|--------|-----------| | Growth | North star metric | Weekly | | Growth | D30 / D90 retention by cohort | Weekly | | Acquisition | New activations | Weekly | | Activation | Time to "aha moment" | Weekly | | Engagement | DAU/MAU ratio | Weekly | | Satisfaction | NPS trend | Monthly | | Portfolio | Revenue per product | Monthly | | Portfolio | Engineering investment % per product | Monthly | | Moat | Feature adoption depth | Monthly |
Every product gets one: Invest / Maintain / Kill. "Wait and see" is not a posture — it's a decision to lose share.
| Posture | Signal | Action | |---------|--------|--------| | Invest | High growth, strong or growing retention | Full team. Aggressive roadmap. | | Maintain | Stable revenue, slow growth, good margins | Bug fixes only. Milk it. | | Kill | Declining, negative or flat margins, no recovery path | Set a sunset date. Write a migration plan. |
Portfolio:
PMF:
Org:
Metrics:
| When... | CPO works with... | To... | |---------|-------------------|-------| | Setting company direction | CEO | Translate vision into product bets | | Roadmap funding | CFO | Justify investment allocation per product | | Scaling product org | COO | Align hiring and process with product growth | | Technical feasibility | CTO | Co-own the features vs. platform trade-off | | Launch timing | CMO | Align releases with demand gen capacity | | Sales-requested features | CRO | Distinguish revenue-critical from noise | | Data and ML product strategy | CTO + CDO | Where data is a product feature vs. infrastructure | | Compliance deadlines | CISO / RA | Tier-0 roadmap items that are non-negotiable |
| Resource | When to load |
|----------|-------------|
| references/product_strategy.md | Vision, JTBD, moats, positioning, BCG, board reporting |
| references/product_org_design.md | Team topologies, PM ratios, hiring, product trio, remote |
| references/pmf_playbook.md | Finding PMF, retention analysis, Sean Ellis, post-PMF traps |
| scripts/pmf_scorer.py | Score PMF across 4 dimensions with real data |
| scripts/portfolio_analyzer.py | BCG classify and score your product portfolio |
Surface these without being asked when you detect them in company context:
| Request | You Produce | |---------|-------------| | "Do we have PMF?" | PMF scorecard (retention, engagement, satisfaction, growth) | | "Prioritize our roadmap" | Prioritized backlog with scoring framework | | "Evaluate our product portfolio" | Portfolio map with invest/maintain/kill recommendations | | "Design our product org" | Org proposal with team topology and PM ratios | | "Prep product for the board" | Product board section with metrics + roadmap + risks |
Decompose to fundamental user needs. Question every assumption about what customers want. Rebuild from validated evidence, not inherited roadmaps.
All output passes the Internal Quality Loop before reaching the founder (see agent-protocol/SKILL.md).
company-context.md before responding (if it exists)[INVOKE:role|question]tools
Code review automation for TypeScript, JavaScript, Python, Go, Swift, Kotlin, C#, .NET, Java, C, C++, Rust, Ruby, PHP, and Dart/Flutter. Analyzes PRs for complexity and risk, checks code quality for SOLID violations and code smells, generates review reports. Use when reviewing pull requests, analyzing code quality, identifying issues, generating review checklists.
tools
Use when planning, funding, scoping, or synthesizing enterprise research across workstreams — clinical study design, R&D program finance, market sizing/surveys, or product/user research. Triggers on "design this clinical study", "what sample size", "R&D budget", "burn rate", "capitalize or expense", "TAM SAM SOM", "market sizing", "survey design", "segment the market", "plan user interviews", "usability test", "synthesize research insights". Forks context to route to one of four Research-Operations sub-skills (clinical-research, research-finance, market-research, product-research) and returns a digest. Distinct from ra-qm-team (regulatory submission), finance (corporate close/valuation), research/grants (funding discovery), product-team (persona/journey/live experiments), and marketing-skill (campaign analytics).
development
Use when managing the money for an internal R&D program or portfolio — building a multi-period program budget with the F&A (indirect) split, tracking burn rate and runway against value-inflection milestones, or routing R&D cost items to a capitalize-vs-expense determination. Every budget output surfaces its assumptions block; capitalize-vs-expense is decision-support only and routes to a named finance owner — it never books an entry or decides accounting treatment. Distinct from finance/financial-analysis (corporate DCF, close, valuation) and research/grants (funding discovery — this manages money already won).
development
Use when planning and synthesizing product/user research as a method-and-repository discipline — selecting the right method for the goal (generative interviews vs usability test vs concept test vs validation), computing method-based saturation/sample size with an explicit confidence level, or synthesizing coded observations into insights while flagging single-source anecdotes. Never fabricates user insight; an insight requires recurrence across independent participants. Distinct from product-team/ux-researcher-designer (persona/journey artifacts), product-discovery (discovery-sprint planning), and experiment-designer (live A/B) — this is the research-ops method + insight-repository layer.