Product Manager Skills is a collection of structured frameworks and guidance designed to equip AI agents and product managers with professional-grade methods for product management work.
The library addresses the problem that generic AI output fails to serve product management needs without shared context and professional judgment. When a PM asks an AI agent to write a requirements document without providing the underlying reasoning and constraints, the result is typically a generic document that stakeholders distrust and engineers cannot act on. The tool solves this by packaging 77 battle-tested frameworks with the reasoning behind each one, the failure modes to avoid, and guidance on when and how to apply them correctly. Each framework is structured as a skill that both humans and AI agents can reference, creating a shared foundation that reduces repetition and guesswork.
The collection covers the full scope of product management work: framing and strategy through problem-framing canvases and positioning statements; stakeholder alignment via identification, mapping, and per-stakeholder engagement planning; customer discovery using Mom Test-style interview preparation and opportunity-solution trees; and prioritization and roadmapping with advisors that recommend the right method based on context. The frameworks are organized by the actual work a PM needs to accomplish rather than by abstract categories. This approach suits teams building products with AI agents, teams that want to standardize their PM processes, and individual PMs seeking to deepen their reasoning about framework selection and application. The tool is explicitly designed to be dual-purpose: it equips agents to perform PM work at a professional level while teaching human PMs the reasoning behind each framework so they can explain, adapt, and teach it to others.
Development activity shows consistent engagement with the core mission. The project maintains a focused scope on product management frameworks rather than expanding into adjacent areas. Work centers on refining and documenting individual skills with their underlying reasoning and application guidance. The codebase reflects a structured approach to organizing frameworks in a way that both humans and agents can navigate and reference reliably.
