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product-manager-toolkit

Score features with RICE and analyze customer interview transcripts.

1|Updated Feb 19, 2026
Search Tags:#product management#roadmap#prioritization#PRD#customer discovery#RICE
One-click install
npx skills add https://github.com/mcauduro0/Macro_Trading --skill product-manager-toolkit-mcauduro0
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: product-manager-toolkit
Source: https://github.com/mcauduro0/Macro_Trading/tree/main/.claude/skills/alireza-product-manager-toolkit
Command: npx skills add https://github.com/mcauduro0/Macro_Trading --skill product-manager-toolkit-mcauduro0

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, scikit-learn, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines product management workflows by providing tools for feature prioritization, customer discovery, and PRD development, reducing guesswork and improving product strategy.

Core Features & Use Cases

  • RICE Prioritization: Score and rank features based on Reach, Impact, Confidence, and Effort to build effective roadmaps.
  • Customer Interview Analysis: Extract pain points, feature requests, and key themes from interview transcripts using NLP.
  • PRD Development: Utilize templates and frameworks to document product requirements clearly and efficiently.
  • Use Case: A product manager can input feature ideas into the RICE prioritizer to decide which ones to focus on next quarter, or analyze customer interview notes to identify the most pressing user needs.

Quick Start

Use the product manager toolkit to prioritize features from the file 'new_features.csv' with a team capacity of 15 person-months.

Frequently Asked Questions about product-manager-toolkit

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

FAQPage Schema
How do I prioritize features using RICE scoring for a product roadmap?▼

RICE scoring prioritizes features by evaluating Reach, Impact, Confidence, and Effort. This skill calculates scores from your feature list and ranks them against a specified team capacity to guide data-driven roadmap decisions.

Can I extract feature requests and pain points from customer interview transcripts?▼

Yes, you can extract pain points and feature requests from customer interview transcripts. This skill applies NLP-driven analysis to identify key themes and pressing user needs from raw qualitative notes.

What is the best way to document product requirements from discovery insights?▼

The best way to document product requirements is using structured PRD templates. This skill provides frameworks to translate customer discovery insights and RICE prioritization outputs into clear product requirement documents.

Does this product management toolkit require pandas and scikit-learn to run?▼

Yes, this product management toolkit requires pandas, numpy, and scikit-learn. These dependencies are necessary to support the underlying data processing and NLP-driven analysis of customer interviews and feature lists.

How do I use a CSV file to calculate feature capacity for my next quarter?▼

You can use a CSV file to calculate feature capacity by inputting it into the RICE prioritizer. This skill evaluates your features against a defined person-month team capacity to determine feasible quarterly roadmap scope.

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