What is the WINNING filter used in this skill?

The WINNING filter is a prioritization framework that scores features based on Pain Intensity, Market Timing, Execution Capability, Strategic Fit, Revenue Potential, and Competitive Moat to identify high-conviction tasks.

Where is my product management data stored?

All data, including competitor profiles, gap analyses, and PRDs, is stored locally in a .pm/ folder at the root of your project for easy versioning and access.

How does the skill prevent duplicate feature requests?

It uses a fuzzy matching algorithm that analyzes title similarity, keyword overlap, and description matches against your existing GitHub Issues before filing a new gap.

Does it require any external tools?

It requires the GitHub CLI (gh) to be installed and authenticated for syncing issues, filing feature requests, and creating PRDs.

Can this skill analyze my existing code?

Yes, the /pm:analyze command scans your project's routes, components, and APIs to build a local product inventory and identify technical moats or debt.

Product Management AI

Name: Product Management AI
Author: ooiyeefei

byooiyeefei

•

133

Collaboration Tools

Streamlines product discovery and backlog management using AI-driven competitor research and the WINNING prioritization framework.

About

This skill transforms Claude into an expert AI Product Manager specifically designed for startup workflows. It automates high-level PM tasks like autonomous competitor scouting, systematic gap analysis, and codebase-aware product inventory. By applying the 'WINNING' filter (Pain × Timing × Execution), it helps teams move from raw signals to high-conviction priorities. The skill features deep GitHub integration for syncing issues, deduplicating feature requests, and generating comprehensive PRDs that bridge the gap between product vision and technical execution.

Key Features

Autonomous competitor landscape scouting and feature categorization
Fuzzy-match deduplication of feature requests against existing GitHub Issues
Local-first product intelligence storage in the .pm/ directory
133 GitHub stars
Systematic gap analysis using the WINNING (Pain, Timing, Execution) prioritization filter
Automated PRD generation with direct syncing to GitHub repositories

Use Cases

Prioritizing a messy backlog into a structured roadmap based on strategic fit and execution capability
Identifying market gaps by researching competitor features and mapping them against your current codebase
Drafting production-ready PRDs that include user stories and acceptance criteria for developer handoff

About

Key Features

Autonomous competitor landscape scouting and feature categorization
Fuzzy-match deduplication of feature requests against existing GitHub Issues
Local-first product intelligence storage in the .pm/ directory
133 GitHub stars
Systematic gap analysis using the WINNING (Pain, Timing, Execution) prioritization filter
Automated PRD generation with direct syncing to GitHub repositories

Use Cases

Prioritizing a messy backlog into a structured roadmap based on strategic fit and execution capability
Identifying market gaps by researching competitor features and mapping them against your current codebase
Drafting production-ready PRDs that include user stories and acceptance criteria for developer handoff