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sitechfromgeorgia
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feature-impact-analyzer

Rank feature ideas using RICE, ICE, and Impact/Effort frameworks with Python calculators.

Updated Aug 23, 2026
Search Tags:#roadmap#prioritization#data-driven#feature backlog#RICE#ICE
One-click install
npx skills add https://github.com/sitechfromgeorgia/georgian-distribution-system --skill feature-impact-analyzer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: feature-impact-analyzer
Source: https://github.com/sitechfromgeorgia/georgian-distribution-system/tree/main/.claude/skills/feature-impact-analyzer
Command: npx skills add https://github.com/sitechfromgeorgia/georgian-distribution-system --skill feature-impact-analyzer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Product teams often struggle to consistently evaluate and rank feature ideas, resulting in misaligned roadmaps and missed opportunities.

Core Features & Use Cases

  • Multi-framework scoring: Apply RICE, ICE, and Impact/Effort matrices to prioritize ideas.
  • KPI alignment: Tie features to retention, growth, and revenue metrics for measurable impact.
  • Tradeoff visualization: Generate 2x2 matrices and visual comparisons to communicate tradeoffs.
  • Quick wins identification: Automatically flag high-impact, low-effort features for fast validation.
  • Automated scoring scripts: Python-based calculators for batch processing and reproducible scoring.

Quick Start

Prepare a list of features with numeric inputs (reach, impact, confidence, effort) and run the provided scripts:

  • To evaluate a single feature:
    • python scripts/calculate_rice.py --reach <val> --impact <val> --confidence <val> --effort <val>
    • python scripts/calculate_ice.py --impact <val> --confidence <val> --ease <val>
  • To evaluate multiple features from a CSV:
    • python scripts/calculate_rice.py --csv features.csv --output results.csv
    • python scripts/calculate_ice.py --csv features.csv --output results.csv

Frequently Asked Questions about feature-impact-analyzer

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

FAQPage Schema
How do I rank features using the RICE prioritization framework?▼

Batch feature prioritization is supported by running the Python scoring scripts with a CSV file input containing your feature backlog data. The calculator processes the list and exports the ranked results to a CSV or JSON file.

What's the best way to prioritize a product roadmap with data-driven scoring?▼

Quick wins are identified automatically by flagging features that score high in impact and low in effort during the prioritization process. This allows product teams to target features for fast validation and immediate value generation.

Can I use Python to calculate ICE scores for multiple features at once?▼

Tradeoff visualization is generated through 2x2 matrices and visual comparisons based on the calculated Impact and Effort scores. This helps product teams communicate prioritization tradeoffs clearly to stakeholders.

How does an Impact/Effort matrix help with feature backlog prioritization?▼

Feature evaluation ties directly to business metrics by aligning features with retention, growth, and revenue KPIs during the scoring process. This ensures that the prioritization outputs support measurable product impact across teams.

Do I need specific dependencies to run these feature prioritization scripts?▼

Quarterly product prioritization is supported by applying the RICE, ICE, or Impact/Effort frameworks to evaluate and rank your accumulated feature backlog. The scripts process the numeric inputs to generate structured, data-driven roadmap decisions.

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