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product-manager-toolkit skill

/skills/.experimental/product/product-manager-toolkit

This skill helps product managers prioritize effectively using RICE, synthesize discoveries, and draft PRDs with templates and guardrails.

This is most likely a fork of the product-manager-toolkit skill from openclaw
npx playbooks add skill vadimcomanescu/codex-skills --skill product-manager-toolkit

Review the files below or copy the command above to add this skill to your agents.

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SKILL.md
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---
name: product-manager-toolkit
description: Comprehensive toolkit for product managers including RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, and go-to-market strategies. Use for feature prioritization, user research synthesis, requirement documentation, and product strategy development.
---

# Product Manager Toolkit

Practical workflows for prioritization, discovery synthesis, and PRD creation.

## Quick Start
- **RICE prioritization**: `scripts/rice_prioritizer.py` (CSV in, ranked list out)
- **Interview analysis**: `scripts/customer_interview_analyzer.py` (transcript in, insights out)
- **PRD templates**: start from `references/prd_templates.md`

## Core Workflows
1) **Prioritize**: collect requests → score with RICE → validate capacity.
2) **Discover**: run interviews → synthesize themes → map to opportunities.
3) **Specify**: choose PRD template → define scope, metrics, acceptance criteria.

## Guardrails
- Always define non-goals.
- Keep metrics measurable and time-bound.
- Separate discovery notes from decisions.

## References
- Extended examples: `references/examples.md`

Overview

This skill is a comprehensive Product Manager Toolkit that packages practical workflows for prioritization, discovery synthesis, and PRD creation. It provides runnable scripts for RICE scoring and interview analysis plus ready-made PRD templates to speed decision-making and documentation. Use it to move from raw requests and research to prioritized roadmaps and clear requirement documents.

How this skill works

The toolkit inspects CSVs of feature requests and runs a RICE prioritizer to produce a ranked list based on reach, impact, confidence, and effort. It analyzes interview transcripts to extract themes, user needs, and opportunity statements. It also supplies PRD templates and step-by-step specification guidance to convert validated opportunities into scoped deliverables with measurable metrics and acceptance criteria.

When to use it

  • When you need to prioritize a backlog of feature requests quickly and consistently
  • When synthesizing customer interviews into actionable themes and opportunity maps
  • When drafting a PRD or scoping a feature with clear success metrics
  • When preparing discovery outputs for stakeholder review or roadmap planning
  • When you need a repeatable, transparent prioritization process for cross-functional teams

Best practices

  • Always capture non-goals alongside scope to prevent scope creep
  • Keep metrics measurable and time-bound for reliable validation
  • Separate raw discovery notes from formal decisions and PRD content
  • Validate RICE inputs with engineering and design before finalizing scores
  • Use interview themes to generate hypothesis-driven experiments, not just feature lists

Example use cases

  • Import backlog CSV to run RICE prioritization and export a ranked roadmap for quarter planning
  • Feed interview transcripts to the analyzer to produce key pain points and opportunity statements
  • Start a new feature PRD from a template, fill scope, metrics, acceptance criteria, and circulation plan
  • Run discovery workshops, synthesize themes, then map top opportunities to prioritized backlog items
  • Create a go-to-market checklist from PRD outputs and success metrics for launch readiness

FAQ

What input formats are required?

Prioritizer accepts CSV with request fields; interview analyzer accepts plain-text transcripts. Templates are Markdown files to copy and edit.

How do I validate RICE scores?

Review scores with engineering and design to confirm effort and feasibility, and adjust confidence based on recent discovery evidence.