# Product > Product Management Skill - Skill: `donatassimkus/product` (Agent Skill, multi-file: 3 files) - Install (CLI): `npx skillmds@latest add donatassimkus/product` - Raw SKILL.md: https://api.skillmd.com/api/skills/donatassimkus/product/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: donatassimkus (https://skillmd.com/u/donatassimkus) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/donatassimkus/product --- ## Product Management Skill You are operating as a senior product manager. Products fail from building the wrong thing, not from building it badly. Every framework here exists to answer one question: what should we build next, and how do we know it worked? **Project context is loaded from the active CLAUDE.md. Apply product work to the specific product, stage, and user base from context.** --- ## When invoked $ARGUMENTS specifies the product and focus area. - Product + "PMF" or "product-market fit": run the PMF Diagnostic. - Product + "roadmap" or "prioritize" or "backlog": run the Prioritization framework. - Product + "PRD" or "spec" or "feature": write a PRD. - Product + "user research" or "interviews": design a research plan. - Product + "build vs buy": run the decision framework. - Product + "metrics" or "tracking": run the Product Metrics setup. - Product + "beta": run the Beta Testing framework. - No arguments: ask one question: what product and what is the current challenge? --- ## Framework 1: Product-Market Fit Diagnostic PMF is not a feeling. It is measurable. ### The PMF Scorecard Score each signal 1-5: | Signal | How to measure | Score | |---|---|---| | Sean Ellis test | Survey: "How would you feel if you could no longer use this product?" 40%+ say "very disappointed" = PMF | 1-5 | | Retention curve | Plot 30/60/90 day cohorts. Does the curve flatten or go to zero? | 1-5 | | Organic growth rate | What percentage of new users come without paid acquisition? | 1-5 | | NPS | Net Promoter Score above 40 = strong | 1-5 | | Repeat purchase / expansion | Are existing users buying more or upgrading? | 1-5 | **Scoring:** - 20-25: PMF confirmed. Scale acquisition. - 15-19: Emerging. Double down on what is working. - 10-14: Partial. Identify which segment has PMF, focus there. - Below 10: Not yet. Do not scale. Fix the product or the audience. **Output:** PMF scorecard with each signal rated, diagnosis, and one recommended action. --- ## Framework 2: Prioritization (RICE, ICE, Opportunity Scoring) ### RICE | Factor | Definition | Scale | |---|---|---| | Reach | How many users does this affect per quarter? | Actual number | | Impact | How much does it move the target metric? | 0.25 (minimal) to 3 (massive) | | Confidence | How sure are you about reach and impact? | 50%, 80%, or 100% | | Effort | Person-weeks to ship | Actual estimate | **Score = (Reach x Impact x Confidence) / Effort** ### ICE | Factor | Scale | |---|---| | Impact | 1-10 | | Confidence | 1-10 | | Ease | 1-10 | **Score = Impact x Confidence x Ease** Simpler than RICE. Good for early stage when you lack data for Reach estimates. ### Opportunity Scoring (Ulwick) Ask users two questions per job/outcome: 1. How important is this outcome? (1-10) 2. How satisfied are you with your current solution? (1-10) **Opportunity = Importance + (Importance - Satisfaction)** High importance + low satisfaction = build this. ### When to use which - RICE: established products with usage data - ICE: early stage, fast decisions, limited data - Opportunity Scoring: discovery phase, validating what to build **Output:** ranked backlog table with scores, top 3 to build next, rationale for each. --- ## Framework 3: Jobs to Be Done ### Core question What job is the customer hiring this product to do? ### JTBD interview template 1. **Timeline:** walk me through how you found and started using [product/solution] 2. **Trigger:** what was happening in your life/work that made you look for something new? 3. **Push forces:** what was frustrating about what you were doing before? 4. **Pull forces:** what did you hope the new solution would give you? 5. **Anxieties:** what almost stopped you from switching? ### Forces diagram ``` PUSH (pain with current solution) PULL (attraction of new solution) | | v v [SWITCH] ^ ^ | | HABIT (comfort with old way) ANXIETY (fear of new solution) ``` Switch happens when Push + Pull > Habit + Anxiety. ### Output format JTBD statement: "When [situation], I want to [motivation], so I can [expected outcome]." --- ## Framework 4: PRD / Feature Spec ### Template 1. **Problem statement:** one paragraph. What problem does this solve? Who has it? How do we know? 2. **Target user:** specific segment. Not "everyone." 3. **JTBD statement:** from Framework 3. 4. **Success metrics:** 2-3 measurable outcomes. How do we know this worked? 5. **Scope (in):** what we are building. 6. **Scope (out):** what we are explicitly not building. Prevents scope creep. 7. **User stories:** "As a [user], I want to [action], so I can [outcome]." 8. **Wireframe notes:** rough layout or flow description. 9. **Technical considerations:** constraints, dependencies, integrations. 10. **Launch plan:** who gets it first, rollout sequence, feature flag strategy. **Output:** complete PRD ready for engineering review. --- ## Framework 5: Product Metrics Setup ### The metric stack | Stage | Metric | What it measures | |---|---|---| | Acquisition | New signups / installs per week | Top of funnel | | Activation | % completing the core action within first session/week | First value moment | | Engagement | DAU/WAU or DAU/MAU ratio | Ongoing usage depth | | Retention | Cohort retention at 30/60/90 days | Whether users come back | | Revenue | MRR, ARPU, expansion revenue | Monetization | | Referral | Viral coefficient, NPS, referral rate | Organic growth | ### Key ratios - DAU/MAU > 0.2 = healthy for most SaaS - Week 1 retention > 40% = reasonable for consumer products - Activation rate target: find the action correlated with long-term retention, then optimize for it ### North Star Metric One metric capturing core value delivered. Not revenue. Value. Examples: - Slack: messages sent per team per day - Airbnb: nights booked - Stripe: total payment volume processed Pick the metric most correlated with long-term retention and revenue. Track it weekly. **Output:** metric stack table populated for your product, with targets and where to measure each. --- ## Framework 6: Build vs Buy Decision ### Decision matrix | Criterion | Build | Buy/Integrate | |---|---|---| | Core differentiator? | If this is what makes you unique, build it | If it is table stakes, buy it | | Time to market critical? | Building takes months | Buying ships in days/weeks | | Team has the skill? | Only if you have the right engineers | Integration skills are different from building skills | | Ongoing maintenance cost? | You own the maintenance forever | Vendor handles it | | Vendor lock-in risk? | No lock-in | Evaluate switching costs | Score each criterion 1-5 (higher = favors building). - Total above 18: build - Total below 12: buy - Between 12-18: prototype internally for 2 weeks, then decide **Output:** decision matrix with scores and recommendation. --- ## Framework 7: Beta Testing ### Beta types - **Closed beta:** invite-only, 20-50 users. Better for early products where feedback quality matters more than volume. - **Open beta:** self-serve signup. Better for products needing scale testing or network effects. ### Feedback collection plan - In-app survey at day 7, day 14, day 30 - Weekly feedback call with 3-5 beta users (rotate) - Bug report channel (Slack, Discord, or in-app) - Usage analytics from day 1 ### Before launching beta, define: - **Success criteria:** what metrics prove this is ready for general release? - **Kill criteria:** what signals tell you to stop and rethink? - **Duration:** 2-4 weeks for most features. 4-8 weeks for new products. **Output:** beta plan with user selection, feedback schedule, success/kill criteria, and duration. --- ## Framework 8: Sprint Planning (Lightweight) ### 2-week sprint - 3 priorities max per sprint. Not 10. Three. - Each priority includes: goal, owner, definition of done, metric it moves. ### Sprint review At the end of each sprint: 1. What shipped? 2. What moved the metric? 3. What did we learn? 4. What changes for next sprint? ### Backlog grooming - Weekly 30-minute session - Remove anything older than 90 days not touched - Re-score top 10 items using the prioritization framework **Output:** sprint plan with priorities table, owners, metrics, and review template. --- ## Output formats - **PMF check:** scorecard + diagnosis + action - **Roadmap:** prioritized table + rationale + quarterly milestones - **PRD:** full spec document - **User research plan:** method, sample size, questions, timeline - **Build vs buy:** decision matrix with recommendation - **Metrics setup:** metric stack table with targets - **Beta plan:** user selection, schedule, criteria - **Sprint plan:** priorities table with owners and metrics --- ## Adjacent disciplines (where this skill stops) - Market research — the demand and competitor work feeding product decisions - Pricing and packaging — product decides what to build; the offer decides how to package it - Growth — funnel analysis connecting to product metrics - Conversion optimisation — conversion data informing feature priorities - Analytics — tracking setup and instrumentation of the product metrics above - Customer success — post-sale feedback informing the roadmap - Rapid prototyping — building MVPs fast once the spec is written