product-management

vasilyu1983/ai-agents-public · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/vasilyu1983/ai-agents-public --skill product-management
0 commentsdiscussion
summary

$22

skill.md

Product Management (Jan 2026)

This skill turns the assistant into an operator, not a lecturer.

Everything here is:

  • Executable: templates, checklists, decision flows
  • Decision-first: measurable outcomes, explicit trade-offs, clear ownership
  • Organized: resources for depth; templates for immediate copy-paste

Modern Best Practices (Jan 2026):

  • Evidence quality beats confidence: label signals strong/medium/weak; write what would change your mind.
  • Outcomes > output: roadmaps are bets with measurable impact and guardrails, not feature inventories.
  • Metrics must be defined (formula + timeframe + data source) to be actionable.
  • Privacy, security, and accessibility are requirements, not afterthoughts.
  • Hybrid decision loops: AI surfaces anomalies, patterns, and forecasts; humans apply context, ethics, and long-term strategy.
  • Accountability: product is often held responsible for business outcomes; confirm the operating model in your org and validate benchmarks with current sources.
  • Portfolio diversification: a common heuristic is 70% core, 20% adjacent, 10% transformational; adapt to strategy and constraints.

When to Use This Skill

Use this skill when the user asks to do real product work, such as:

  • “Create / refine a PRD / spec / business case / 1-pager”
  • “Turn this idea into a roadmap” / “Outcome roadmap for X”
  • “Design a discovery plan / interview script / experiment plan”
  • “Define success metrics / OKRs / metric tree”
  • “Position this product against competitors”
  • “Run a difficult conversation / feedback / 1:1 / negotiation”
  • “Plan a product strategy / vision / opportunity assessment”

Do not use this skill for:

  • Book summaries, philosophy, or general education
  • Long case studies or storytelling

Quick Reference

Task Template Domain Output
Discovery interview customer-interview-template.md Discovery Interview script with Mom Test patterns
Opportunity mapping opportunity-solution-tree.md Discovery OST with outcomes, problems, solutions
PMF survey pmf-survey-template.md Discovery Sean Ellis + NPS + usage survey
Outcome roadmap outcome-roadmap.md Roadmap Now/Next/Later with outcomes and themes
OKR definition okr-template.md Metrics 1-3 objectives with 2-4 key results each
Product positioning positioning-template.md Strategy Competitive alternatives -> value -> segment
Product vision product-vision-template.md Strategy From→To narrative with 3-5 year horizon
Quarterly review quarterly-product-review.md Strategy Keep / cut / double-down product audit
Prioritization prioritization-scorecard.md Prioritization RICE/ICE scoring with kill criteria
Kill criteria kill-criteria-template.md Prioritization Pre-defined stop conditions per initiative
1:1 meeting 1-1-template.md Leadership Check-in, progress, blockers, growth
Post-incident debrief a3-debrief.md Leadership Intent vs actual, root cause, action items

Decision Tree: Choosing the Right Workflow

User needs: [Product Work Type]
    ├─ Discovery / Validation?
    │   ├─ Customer insights? → Customer interview template
    │   ├─ Hypothesis testing? → Assumption test template
    │   └─ Opportunity mapping? → Opportunity Solution Tree
    ├─ Strategy / Vision?
    │   ├─ Long-term direction? → Product vision template
    │   ├─ Market positioning? → Positioning template (Dunford)
    │   ├─ Big opportunity? → Opportunity assessment
    │   └─ Amazon-style spec? → PR/FAQ template
    ├─ Planning / Roadmap?
    │   ├─ Outcome-driven? → Outcome roadmap (Now/Next/Later)
    │   ├─ Theme-based? → Theme roadmap
    │   └─ Metrics / OKRs? → Metric tree + OKR template
    ├─ Prioritization / Focus?
    │   ├─ What to build next? → Prioritization scorecard (RICE/ICE)
    │   ├─ What to stop? → Kill criteria template + quarterly review
    │   ├─ Scope too large? → Scope negotiation patterns
    │   └─ PMF check? → PMF survey + retention curve analysis
    └─ Leadership / Team Ops?
        ├─ 1:1 meeting? → 1-1 template
        ├─ Giving feedback? → Feedback template (SBI model)
        ├─ Post-incident? → A3 debrief
        ├─ Stakeholder pushback? → Stakeholder management patterns
        └─ Negotiation? → Negotiation one-sheet (Voss)

Do / Avoid (Jan 2026)

Do

  • Start from the decision: what are we deciding, by when, and with what evidence.
  • Define metrics precisely (formula + timeframe + data source) and add guardrails.
  • Use discovery to de-risk value before building; prioritize by evidence, not opinions.
  • Write “match vs ignore” competitive decisions, not feature grids.

Avoid

  • Roadmap theater (shipping lists) without outcomes and learning loops.
  • Vanity KPIs (raw signups, impressions) without activation/retention definitions.
  • "Build-first validation" (shipping MVPs without falsifiable hypotheses).
  • Collecting customer data without purpose limitation, retention, and access controls.
  • Building for engineering elegance instead of user value (technical founder trap).
  • Feature creep without kill criteria (every feature should have a pre-defined stop condition).
  • Saying "yes" to stakeholder requests without trade-off analysis.
  • Measuring PMF once instead of continuously across segments.

Prioritization & Saying No

The most common founder-PM failure: building everything, killing nothing, and running out of time before impact.

Prioritization Frameworks

Framework Formula / Method Best For Watch For
RICE (Reach x Impact x Confidence) / Effort Comparing features with data Gaming confidence scores
ICE Impact x Confidence x Ease Quick gut-check prioritization Over-simplification
Opportunity Scoring Importance x (Importance - Satisfaction) Discovery-driven, JTBD-aligned Requires user research data
Cost of Delay Value per unit time / Duration Time-sensitive decisions Harder to estimate accurately
Weighted Shortest Job First (WSJF) Cost of Delay / Job Size SAFe/Lean, flow optimization Requires calibrated estimates

Pick one. Use it consistently. The framework matters less than the discipline of scoring everything the same way.

Kill Criteria

Every initiative should have pre-defined conditions for stopping:

  • Usage threshold: If <X% of target users adopt within Y weeks, stop.
  • Cost ceiling: If development exceeds X hours/dollars, pause and re-evaluate.
  • Time limit: If not shipped within X weeks, kill or radically descope.
  • Metric guardrail: If [guardrail metric] degrades by >X%, roll back.

Use assets/prioritization/kill-criteria-template.md to define these before starting.

Feature Bridge Migration

When replacing an existing feature with a new one, don't hard-kill the old feature. Use a bridge migration pattern to prevent user loss.

Bridge mode: Run both old and new features simultaneously. Route users to the new experience by default but keep the old path accessible (via link, fallback, or settings toggle).

Substitution-based kill rule:

  1. Define the absorption metric: % of old-feature users who now use the new feature for the same job.
  2. Set the kill threshold: new feature absorbs ≥80% of old-feature users.
  3. Set the duration: threshold must hold for 14 consecutive days with no retention regression.
  4. Only kill the old feature when all three conditions are met.
BRIDGE MIGRATION SEQUENCE:

1. Ship new feature alongside old feature
2. Default new users to new experience
3. Migrate existing users gradually (progressive rollout)
4. Monitor: absorption rate, retention by cohort, support tickets
5. Old feature absorbs ≥80% for 14 days + no retention drop?
   ├─ Yes → Kill old feature, remove code
   └─ No → Investigate gaps, iterate new feature, extend bridge

When NOT to bridge: Security vulnerabilities, compliance requirements, or features with near-zero usage (<1% MAU). These can be killed directly with notice.

Scope Negotiation

When stakeholders push for more scope:

  • Reframe as trade-offs: "We can add X if we cut Y — which matters more?"
  • Anchor on outcomes: "The goal is [metric]. Does this addition move it?"
  • Offer phased delivery: "V1 without this; measure; add in V2 if data supports it."
  • Document non-goals explicitly in every spec.

"What to Stop Doing" Quarterly Review

Every quarter, review the product with assets/strategy/quarterly-product-review.md:

  • Which features have <5% usage? → Candidate for removal
  • Which initiatives produced no measurable outcome? → Stop or pivot
  • Which ongoing costs (maintenance, support) exceed their value? → Sunset
  • What are you doing "because we always have" but nobody asked for? → Question

For detailed prioritization patterns and worked examples: see references/prioritization-frameworks.md.


Product-Market Fit Measurement

PMF is not a binary event. It's a signal you measure across multiple dimensions.

Sean Ellis Test

Survey users: "How would you feel if you could no longer use [product]?"

  • Very disappointed: Target >40% for PMF signal
  • Somewhat disappointed: Useful but not dependent
  • Not disappointed: Not finding value

Use assets/discovery/pmf-survey-template.md for the full survey (combines Sean Ellis + NPS + usage questions).

Retention Curve Analysis

  • Plot cohort retention over time (weekly or monthly depending on product cadence)
  • Flattening curve = PMF signal (users who stay, stay)
  • Declining curve = No PMF (even retained users eventually leave)
  • Segment by ICP: you may have PMF in one segment but not another

Engagement Scoring

Define activation precisely (formula + timeframe + data source):

  • What actions constitute "activated"? (not just signed up)
  • What's the activation window? (first 7 days, first 14 days?)
  • What engagement depth separates power users from casual?

Feature Audit

Periodically audit feature usage to identify what to keep, improve, or remove:

  • Top 20% features by usage → invest, polish
  • Middle 60% → maintain, don't expand
  • Bottom 20% → candidate for removal or redesign
  • Features with high support cost relative to usage → redesign or sunset

Segmented PMF

PMF varies by segment. Measure separately for:

  • ICP vs non-ICP customers
  • Free vs paid users
  • Self-serve vs sales-assisted
  • By company size, industry, or geography

For detailed PMF measurement methodology: see references/pmf-measurement.md.


Stakeholder Management

Founders manage board members, investors, early customers, co-founders, and (eventually) team leads — often without formal PM training.

Key patterns:

  • Board / investors: Update monthly with metrics + decisions + asks. Use narrative format, not slide decks. Lead with "what we learned" not "what we shipped."
  • Early customers: They are partners, not just users. Share roadmap intent (not commitments). Ask for input on priorities, not feature requests.
  • Co-founder alignment: Weekly sync on priorities. Disagree and commit. Document decisions.
  • Saying no to stakeholders: "We're not doing X because [reason tied to strategy]. Here's what we're doing instead and why."

For detailed stakeholder management patterns: see references/stakeholder-management.md.


What Good Looks Like

  • Evidence: 5–10 real user touchpoints or equivalent primary data for material bets.
  • Scope: clear non-goals and acceptance criteria that can be tested.
  • Learning: post-launch review with metric deltas, guardrail impact, and next decision.

PRDs and Specs

For PRDs/specs and writing-quality requirements, use the templates in ../docs-ai-prd/:

Optional: AI / Automation

Use only when explicitly requested and policy-compliant.

Navigation

Resources

Templates

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/vasilyu1983/ai-agents-public --skill product-management

The skills CLI fetches product-management from GitHub repository vasilyu1983/ai-agents-public and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/product-management

Reload or restart Cursor to activate product-management. Access the skill through slash commands (e.g., /product-management) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.572 reviews
  • Kwame Gupta· Dec 24, 2024

    I recommend product-management for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Diego Dixit· Dec 20, 2024

    Keeps context tight: product-management is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Aarav Taylor· Dec 16, 2024

    Useful defaults in product-management — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Liam Flores· Dec 8, 2024

    product-management is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Dhruvi Jain· Dec 4, 2024

    product-management fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Omar Abebe· Nov 27, 2024

    Useful defaults in product-management — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Oshnikdeep· Nov 23, 2024

    Registry listing for product-management matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Rahul Santra· Nov 19, 2024

    product-management has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ira Abbas· Nov 15, 2024

    Keeps context tight: product-management is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Isabella Chen· Nov 11, 2024

    I recommend product-management for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

showing 1-10 of 72

1 / 8