feature-prioritization

Rank product features using an auditable Impact × Confidence × Effort scoring matrix in SQL.

42|9|Updated Mar 16, 2026
One-click install
npx skills add https://github.com/drvoss/everything-copilot-cli --skill feature-prioritization-drvoss
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: feature-prioritization
Source: https://github.com/drvoss/everything-copilot-cli/tree/main/skills/product/feature-prioritization
Command: npx skills add https://github.com/drvoss/everything-copilot-cli --skill feature-prioritization-drvoss

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

backlog prioritization for product features can be subjective; this skill provides a reproducible scoring method to rank items using an Impact × Confidence × Effort matrix with an auditable SQL trail.

Core Features & Use Cases

  • Structured prioritization: Rank features using a 1-5 score across Impact, Confidence, and Effort, with a final computed score.
  • Auditability: All decisions are traceable in SQL, enabling review and governance during sprint planning.
  • Workflow support: Use during backlog refinement, sprint planning, and roadmap scoping to surface high-value items.

Quick Start

Provide a simple backlog of features and have the system score and sort them for sprint planning.

Frequently Asked Questions about feature-prioritization

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I prioritize product backlog features with an auditable scoring matrix?▼

Prioritize product features by scoring each item across Impact, Confidence, and Effort dimensions using a 1-5 scale, then sorting by the computed result. This creates a reproducible, auditable trail for backlog grooming and sprint planning.

What is the best way to track feature prioritization decisions in SQL?▼

Track feature prioritization decisions by storing individual Impact, Confidence, and Effort scores alongside computed results within a defined SQL schema. This establishes an auditable SQL trail for backlog review and sprint planning governance.

Do I need a defined SQL schema to use the Impact Confidence Effort scoring workflow?▼

Yes, this feature prioritization workflow requires a defined SQL schema to store feature metadata, individual dimension scores, and computed results. The SQL schema enables the auditable trail needed for sprint planning governance.

Can I use this feature scoring matrix for sprint planning across multiple product areas?▼

Yes, you can apply the scoring matrix to sprint planning across product areas where features vary in impact and feasibility. The 1-5 scoring scales consistently across diverse backlog items to surface high-value work.

How does the Impact Confidence Effort matrix rank backlog items?▼

The matrix ranks backlog items by assigning a 1-5 score to Impact, Confidence, and Effort, then computing a final weighted result. This surfaces high-value features for sprint planning while maintaining a traceable SQL audit trail.