Product-Manager-Skills and productskills
These are competitors offering overlapping product management frameworks for AI agents, with A providing a broader battle-tested methodology across multiple AI platforms while B focuses on narrower specific workflows (discovery through PRD writing).
About Product-Manager-Skills
deanpeters/Product-Manager-Skills
Product Management skills framework built on battle-tested methods for Claude Code, Cowork, Codex, and AI agents.
Organizes 46 battle-tested product management frameworks (from Teresa Torres, Geoffrey Moore, Amazon) alongside 6 command workflows, designed to teach PMs the reasoning while enabling AI agents to execute—structured as reusable skills for Claude Code, Cursor, n8n, and other platforms. Features trigger-based skill discovery via Streamlit UI and CLI, pedagogic-first design that prioritizes learning over brevity, and multi-platform integration (Claude Desktop, slash commands, Python agents). Includes frameworks for opportunity hunting, validation scaffolding, and rapid hypothesis testing paired with agent-executable prompts.
About productskills
assimovt/productskills
Product skills for AI agents — discovery, strategy, prioritization, and PRD writing
Encodes 14 established product frameworks (Mom Test, Shape Up, Obviously Awesome, JTBD) as 50-150 line markdown skills for Claude, Cursor, and other AI coding agents. Installable via CLI, plugin marketplace, or as git submodule, with skills organized across discovery, strategy, prioritization, and execution phases. Evidence-first approach emphasizing measurable outcomes, scope boundaries, and hypothesis-driven decisions over feature-centric planning.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work