Mmcp.market

prioritize-features skill

by phuryn·phuryn/pm-skills·27k stars·MIT

Prioritize a backlog of feature ideas based on impact, effort, risk, and strategic alignment with top 5 recommendations. Use when prioritizing a feature backlog, making scope decisions, or ranking product ideas.

A100/100content scan

Is the prioritize-features skill safe?

Clean: nothing in its files matched our rules. We read 1 file in the folder on 2026-09-28.

No findings.

Install the prioritize-features skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description. 

git clone --depth 1 https://github.com/phuryn/pm-skills.git /tmp/pm-skills
mkdir -p ~/.claude/skills
cp -r /tmp/pm-skills/pm-product-discovery/skills/prioritize-features ~/.claude/skills/prioritize-features
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

Prioritize Feature Backlog

Evaluate and rank a backlog of feature ideas to identify the top 5 to pursue.

Context

You are helping prioritize features for $ARGUMENTS.

If the user provides files (spreadsheets, backlogs, opportunity assessments), read and analyze them directly.

Domain Context

For framework selection guidance, see the prioritization-frameworks skill. Key recommendations:

Opportunity Score (Dan Olsen, The Lean Product Playbook) is recommended for evaluating customer problems: Opportunity Score = Importance × (1 − Satisfaction), normalized to 0–1. High Importance + low Satisfaction = best opportunities. Prioritize problems (opportunities), not solutions.

ICE is recommended for quick scoring of initiatives: Impact (Opportunity Score × # Customers) × Confidence × Ease. RICE adds Reach as a separate factor for larger teams.

Instructions

The user will describe their product objective, desired outcomes, and provide feature ideas. Work through these steps:

  1. Understand priorities: Confirm the product objective and success metrics.
  1. Evaluate each feature against:
  • Impact: How much does it move the needle on desired outcomes? Consider Opportunity Score if customer data is available.
  • Effort: How much development, design, and coordination is required?
  • Risk: How much uncertainty exists? What assumptions need testing?
  • Strategic alignment: How well does it fit the product vision and current goals?
  1. Recommend the top 5 features with:
  • Clear ranking (1-5)
  • Brief rationale for each selection
  • Key trade-offs considered
  • What was deprioritized and why
  1. Present as a prioritization table if helpful.

Think step by step. Save as markdown if the output is substantial.

Further Reading

  • Kano Model: How to Delight Your Customers Without Becoming a Feature Factory
  • The Product Management Frameworks Compendium + Templates
  • Continuous Product Discovery Masterclass (CPDM) (video course)

More skills from phuryn/pm-skills

  • Aab-test-analysisAnalyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations. Use when evaluating experiment results, checking if a test reached significance, interpreting split test data, or deciding whether to ship a variant.
  • Aanalyze-feature-requestsAnalyze and prioritize a list of feature requests by theme, strategic alignment, impact, effort, and risk. Use when reviewing customer feature requests, triaging a backlog, or making prioritization decisions.
  • Aansoff-matrixGenerate an Ansoff Matrix analysis mapping growth strategies across market penetration, market development, product development, and diversification. Use when considering growth options, planning market expansion, or evaluating strategic growth paths.
  • Abeachhead-segmentIdentify the first beachhead market segment for a product launch. Evaluates segments against burning pain, willingness to pay, winnable market share, and referral potential. Use when choosing a first market, targeting an initial customer segment, or planning market entry strategy.
  • Abrainstorm-experiments-existingDesign experiments to test assumptions for an existing product — prototypes, A/B tests, spikes, and other low-effort validation methods. Use when validating assumptions, testing feature ideas cheaply, or planning product experiments.
  • Abrainstorm-experiments-newDesign lean startup experiments (pretotypes) for a new product. Creates XYZ hypotheses and suggests low-effort validation methods like landing pages, explainer videos, and pre-orders. Use when validating a new product idea, creating pretotypes, or testing market demand.
  • Abrainstorm-ideas-existingBrainstorm product ideas for an existing product using multi-perspective ideation from PM, Designer, and Engineer viewpoints. Use when generating new feature ideas, brainstorming solutions for an identified opportunity, or ideating with a product trio.
  • Abrainstorm-ideas-newBrainstorm feature ideas for a new product in initial discovery from PM, Designer, and Engineer perspectives. Use when starting product discovery for a new product, exploring features for a startup idea, or doing initial ideation.
  • Abrainstorm-okrsBrainstorm team-level OKRs aligned with company objectives — qualitative objectives with measurable key results. Use when setting quarterly OKRs, aligning team goals with company strategy, drafting objectives, or learning how to write effective OKRs.
  • Abusiness-modelGenerate a Business Model Canvas with all 9 building blocks. Use when creating a business model, documenting how a business creates value, or analyzing an existing business model.
  • Acode-reviewReview code for actionable defects. Correctness is the core; performance and security are optional sub-cases of the same engine. Anchors on agreements between participants across a boundary, forces a violating execution, and refutes every candidate before reporting. Use when asked to review changes, find bugs, audit a codebase, or check whether a fix is safe.
  • Acohort-analysisPerform cohort analysis on user engagement data — retention curves, feature adoption trends, and segment-level insights. Use when analyzing user retention by cohort, studying feature adoption over time, investigating churn patterns, or identifying engagement trends.

All agent skills → · MCP servers