Convert Product Requirement Documents into sequenced Lovable prompts with phase-driven deliverables.
npx skills add https://github.com/jumski/dotfiles --skill lovable-prompts
Please help me install this Agent Skill. Skill: lovable-prompts Source: https://github.com/jumski/dotfiles/tree/main/claude/skills/lovable-prompts Command: npx skills add https://github.com/jumski/dotfiles --skill lovable-prompts
What problem does it solves? This Skill transforms complex Product Requirement Documents (PRDs) into a sequence of clear, incremental, and human-verifiable prompts for AI development. It makes implementation predictable and efficient, reducing development cycles and ensuring alignment with requirements.
Convert the attached PRD file 'new_dashboard_prd.md' into a sequence of Lovable prompts.
High-intent search queries and answers about installing and using this skill.
Converting a PRD into incremental prompts breaks requirements into sequenced phases: knowledge base setup, frontend mocks, backend integration, and polish. Each prompt includes self-contained deliverables, mock data, and human-verifiable checklists, enabling predictable AI-guided development without rework.
Frontend-first prompt structure prioritizes UI components with dummy data before backend logic. This approach validates designs early and reduces integration friction. Sequential prompting with explicit deliverables and "Do NOT modify" constraints keeps AI output aligned with requirements.
Yes. Automated PRD-to-prompt conversion applies the CLEAR framework to generate numbered, phase-driven prompts with mock data, integration syntax for external services, and verification checklists. This eliminates manual prompt engineering and ensures consistent, requirement-aligned output.
Each prompt includes human-verifiable checklists tied to specific deliverables, allowing you to validate output incrementally. Sequential phases—setup, frontend mocks, backend, polish—create natural validation gates where requirements map to concrete, testable artifacts.
PRDs convert most effectively when structured by feature or module. The prompt generation process applies the CLEAR framework to organize requirements into phase-driven sequences with explicit file naming, mock data specifications, and integration points marked with backticks.
Yes. Incremental, sequenced prompts with self-contained deliverables and upfront verification checklists reduce back-and-forth cycles. Frontend mocks enable early validation, and explicit constraints minimize rework, making development predictable and faster.
lluppesmsGenerates structured specification documents Templates for AI consumption and development workflows.
u9401066Validate feature delivery completeness across code, tests, and documentation before release.
bennybennisonPackage mocked frontends into structured handoffs with branch references and artifact paths for downstream teams.
marchattonRun verification checks before and after incremental code implementation with PRD JSON updates.
