Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
105 skills found
AI-native product management tool for startups. Features automated competitor research, gap analysis using the WINNING filter, PRD generation, and GitHub Issues integration for prioritized, signal-based roadmap planning.
Expert AI-powered PM resume review and tailoring against 10 industry best practices, including the XYZ+S formula, keyword optimization, and impact-driven structure.
Agile project management expert for sprint planning, risk mitigation, and stakeholder alignment in software engineering teams.
Plan mode on steroids. Push engineers to think with a product mindset before building with structured intake and concrete technical options.
Strategic leadership toolkit for Heads of Product. Generate OKR cascades, conduct quarterly planning, perform competitive analysis, define product vision, and build team scaling proposals.
A framework for software teams and AI agents to prevent feature creep, enforce scope discipline, and ship focused MVPs by applying strict validation, backlog hygiene, and clear decision-making processes.
Structured AI-guided research and market validation for new app ideas. Automates competitor analysis, technical feasibility, and MVP scoping.
Context Engineering agent skill to initialize, generate, and execute comprehensive implementation blueprints (PRPs) for one-pass software development.
Create a comprehensive product strategy using the 9-section Product Strategy Canvas to define your vision, segments, value propositions, and defensibility.
A structured PRD generator for vibe-coding MVPs. It guides you through defining product requirements, target audiences, and success metrics, ensuring a clear foundation for your development workflow.
Plan features through an interactive, multi-step process that generates comprehensive Product Requirements Documents (PRDs) with user stories, acceptance criteria, and technical specifications.
Frame core customer problems, supporting evidence, and success hypotheses to ensure discovery work is grounded in data before solutioning begins.