cpo-advisor

Overview of cpo-advisor skill

What cpo-advisor is for

cpo-advisor is a product leadership skill for strategic Product Management work: product vision, portfolio strategy, product-market fit, product organization design, and board-level product narratives. It is best used when the question is “what should the company build, fund, stop, or reorganize around?” rather than “how should this feature behave?”

Best-fit users and decisions

The cpo-advisor skill fits founders, CPOs, VP Product leaders, product ops teams, and senior PMs preparing strategy reviews. It is especially useful for scaling companies that have more than one product line, unclear PMF signals, too many roadmap commitments, or a product org that no longer matches the business stage.

What makes it different from a generic prompt

The repository includes practical reference material and two helper scripts, not just a role prompt. references/pmf_playbook.md covers segmentation, retention curves, Sean Ellis-style PMF signals, and customer research. references/product_strategy.md covers JTBD, positioning, portfolio management, and board reporting. references/product_org_design.md maps team topologies to product organizations. The scripts add structured scoring for PMF and portfolio analysis.

Where cpo-advisor is not the right fit

Do not install cpo-advisor if you mainly need UI copy, sprint ticket writing, feature acceptance criteria, or tactical backlog grooming. It can inform roadmap strategy, but it is intentionally scoped above feature-level execution.

How to Use cpo-advisor skill

cpo-advisor install and repository path

Install from the GitHub skill repository with:

npx skills add alirezarezvani/claude-skills --skill cpo-advisor

The source path is:

c-level-advisor/skills/cpo-advisor

After install, start with SKILL.md, then read the supporting files in this order: references/product_strategy.md, references/pmf_playbook.md, references/product_org_design.md, then inspect scripts/pmf_scorer.py and scripts/portfolio_analyzer.py if you want numeric inputs.

Inputs that produce better cpo-advisor usage

Strong prompts give the skill enough business context to choose the right product leadership frame. Include:

• Company stage, business model, and market
• Main product lines or segments
• Current product goal: growth, retention, expansion, focus, turnaround, org design
• Available metrics: retention, DAU/MAU, NPS, revenue, market share, churn, referral rate
• Current constraints: engineering capacity, sales commitments, runway, enterprise contracts
• Decision needed: invest, maintain, kill, reposition, reorganize, or report to board

Weak prompt:

Help with product strategy.

Stronger prompt:

Use cpo-advisor for Product Management. We are a B2B SaaS company at $12M ARR with three product lines. Core product has 42% D30 retention, add-on product has high sales demand but low activation, and a new AI workflow has no clear buyer yet. Engineering capacity is split 55/30/15. Recommend a portfolio strategy, what to fund or stop, and how to explain it in a board update.

Practical workflow for PMF and portfolio work

For PMF analysis, read references/pmf_playbook.md before asking for recommendations. If you have real metrics, run:

python scripts/pmf_scorer.py --input data.json

Use the script output as evidence, then ask the skill to interpret what the score means for segmentation, roadmap focus, and GTM risk.

For portfolio decisions, prepare one JSON entry per product or business line, then run:

python scripts/portfolio_analyzer.py --input data.json

The analyzer classifies products using BCG-style logic and investment recommendations. Treat the result as a starting point, not an automatic decision; add qualitative context such as strategic option value, customer concentration, platform dependencies, or regulatory commitments.

Prompt pattern for board-ready outputs

A reliable cpo-advisor guide prompt is:

Act as cpo-advisor. Context: [company, stage, model]. Decision: [what must be decided]. Evidence: [metrics, customer signals, revenue, retention, capacity]. Constraints: [time, people, commitments]. Produce: 1) diagnosis, 2) strategic options, 3) recommended choice, 4) risks and counterarguments, 5) board-ready summary.

This structure helps the skill avoid generic strategy language and produce decision-ready output.

cpo-advisor skill FAQ

Is cpo-advisor for Product Management beginners?

Yes, if the user is working on strategic Product Management questions and can provide business context. Beginners may need to read the reference files first because the skill assumes concepts such as PMF, retention curves, JTBD, portfolio allocation, and product team topology.

How is cpo-advisor different from asking Claude directly?

A direct prompt can produce useful advice, but cpo-advisor gives the agent a consistent product executive frame plus repository-backed references and scripts. That matters when you need repeatable analysis across PMF scoring, portfolio prioritization, product org design, and board communication.

Does cpo-advisor replace product analytics tools?

No. The scripts are lightweight decision aids, not a replacement for Amplitude, Mixpanel, Looker, warehouse analysis, or customer research. The value is in converting product evidence into leadership decisions. You still need accurate source data and judgment.

When should I not use cpo-advisor?

Avoid it for narrow delivery work such as writing Jira tickets, designing one onboarding screen, estimating engineering tasks, or creating a feature spec without strategic context. Use it when the question affects product direction, investment allocation, PMF confidence, org structure, or executive reporting.

How to Improve cpo-advisor skill

Improve cpo-advisor results with sharper evidence

The biggest quality driver is evidence specificity. Replace vague claims like “retention is weak” with cohort data, segment names, churn reasons, activation rates, win/loss notes, and customer quotes. If data is incomplete, say what is missing so the skill can separate evidence from assumptions.

Common failure modes to prevent

cpo-advisor can become too high-level if the prompt lacks constraints. Prevent this by naming the decision owner, time horizon, capacity limit, and what cannot change. For example: “We cannot add headcount for two quarters” or “Enterprise commitments require maintaining Product A through Q4.” These constraints force tradeoff-aware recommendations.

Iterate after the first output

After the first answer, ask for a second pass with a specific lens:

• “Challenge the recommendation as a skeptical CFO.”
• “Rewrite this as a board slide narrative.”
• “Convert the strategy into three portfolio allocation scenarios.”
• “Identify which assumptions must be validated in the next 30 days.”
• “Map the recommended org design to current teams and hiring gaps.”

This turns a broad advisory response into an operating plan.

Customize the skill for your product context

To improve long-term cpo-advisor usage, add internal examples outside the upstream repo: your north star metric, current portfolio taxonomy, board reporting format, PMF thresholds by product type, and product team structure. Keep custom context separate from the original files so updates remain easy to review.