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product-manager-toolkit

Prioritize features with RICE scoring and analyze customer interview transcripts.

Updated Jun 5, 2025
Search Tags:#product management#user research#prioritization#feature planning#PRD#RICE framework
One-click install
npx skills add https://github.com/wangzitian0/finance_report --skill product-manager-toolkit-wangzitian0
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: product-manager-toolkit
Source: https://github.com/wangzitian0/finance_report/tree/main/.opencode/skills/professional/product-management
Command: npx skills add https://github.com/wangzitian0/finance_report --skill product-manager-toolkit-wangzitian0

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires csv, re, json, argparse, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines product management workflows by providing tools for data-driven decision-making, from feature prioritization to user research synthesis.

Core Features & Use Cases

  • Feature Prioritization: Use the RICE framework to objectively score and rank potential features.
  • User Research Analysis: Extract key insights, pain points, and feature requests from customer interviews.
  • Documentation Templates: Leverage PRD templates for clear and comprehensive requirement documentation.
  • Use Case: A product manager needs to decide which features to build next. They can use the RICE prioritizer script with their feature backlog to get an objective ranking, then use the interview analyzer to validate the underlying user needs.

Quick Start

Use the product-manager-toolkit skill to prioritize features from the file 'my_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 the RICE framework?▼

Feature prioritization with the RICE framework involves scoring potential features based on Reach, Impact, Confidence, and Effort. You can process a CSV file containing your feature backlog through the Python script to calculate an objective ranking.

How do I extract insights from customer interview transcripts?▼

User research analysis extracts key insights, pain points, and feature requests from customer interview transcripts. The Python script processes the raw text to synthesize structured user needs for validation.

What format should my feature backlog be in for RICE prioritization?▼

Your feature backlog should be formatted as a CSV file to run the RICE prioritization script. The script parses the CSV data to score and rank potential features based on your specified team capacity.

Can I generate Product Requirements Documents with this toolkit?▼

Yes, you can generate Product Requirements Documents using the included Markdown templates. These PRD templates provide a structured format to define requirements clearly after prioritizing features and validating user needs.

Does the RICE prioritizer account for team capacity constraints?▼

Yes, the RICE prioritizer script accounts for team capacity constraints. You can specify your team's capacity, such as 15 person-months, to ensure the objective feature ranking aligns with available development resources.

How does user research analysis integrate with feature planning?▼

User research analysis validates the underlying needs of prioritized features. You can extract insights from customer interviews to ensure that the objectively ranked features from your RICE scoring address actual user pain points.

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