Pareto Desk - pick a design from your Pareto front, then refine it with pymoo

Paste the evaluated designs from an optimization run or design sweep (objectives, constraints, variables). The browser computes the feasible Pareto front with pymoo semantics - non-dominated sorting, crowding distance, hypervolume, pseudo-weight and ASF picks, verified against pymoo 0.6.2 - and plots it, free. A paid run writes a trade-off decision (a shortlist with what each design gives up) or a pymoo script that refines the search and writes results back for the next round. Derived from the agent skill @k-dense-ai/pymoo (k-dense-ai/scientific-agent-skills, K-Dense Inc.).

Every public app is built from a security-scanned skill and must pass a clean scan — skill and frontend — before it can be listed. Have a skill of your own? Turn it into an app — or read the step-by-step walkthrough.