product-manager-toolkit

To prioritize features using the RICE framework, you run the included Python script with a CSV file of your feature ideas. The script calculates Reach, Impact, Confidence, and Effort scores to output an objective ranking of potential features.

Yes, you can extract pain points and feature requests from customer interview transcripts. The included Python analyzer script processes interview text to synthesize key user research insights and validate product decisions.

The best way to document product requirements is using the provided Markdown PRD templates. These templates support comprehensive requirement documentation and product discovery frameworks to structure your go-to-market strategy.

Yes, the product manager toolkit requires Python3 to run the prioritization scripts. You need a Python3 environment to execute the RICE scoring and customer interview analysis scripts provided in the toolkit.

You can rank features against a specific team capacity limit by passing your feature CSV and capacity constraint to the prioritization script. For example, you can input a team capacity of 15 person-months per quarter to filter ranked features.