The Lovable Prompt
A spec-generation skill that turns a rough app idea into a structured, opinionated Lovable.dev build prompt — with defined data models, user flows, edge states, and acceptance tests. This site was built using it.
PROBLEM
Lovable rewards specific, structured prompts and punishes vague ones. But the natural way to describe a new app idea is rough and conversational — by the time you've manually expanded it into data models, flows, edge states, and acceptance tests, you've spent an hour before the first prompt lands.
SOLUTION
The Lovable Prompt skill ingests a rough idea, runs structured elicitation to fill the gaps, then emits a full build spec organized exactly the way Lovable's docs recommend: data model first, user flows next, explicit edge states, and acceptance tests at the end. The output drops into Lovable as a single prompt and produces a coherent first build.
BENEFITS
- Rough idea → ship-ready prompt in one pass — no manual spec writing
- Opinionated structure (data → flows → edges → tests) matches Lovable's strongest prompting patterns
- Acceptance tests make 'is this done?' answerable before the first build
- This portfolio site was built end to end using it
CHALLENGES & WHAT I'D IMPROVE
Knowing when to stop eliciting — too few questions produces vague specs, too many turn it into an interview. Next iteration: a stakes-based questioning depth (more questions for production apps, fewer for throwaway prototypes) and a built-in iteration mode for refining a spec after the first build round.