Expert AMPL debugger for infeasibility, unboundedness, IIS, conflict analysis, and solve failures. Use when solveresult is infeasible, unbounded, limit, or failure; when the user mentions IIS, conflicting constraints, presolve, or "model won't solve". Readonly diagnosis — fixes are suggestions until verified.
Optimization expert that explains AMPL models: variable-constraint linkage, logical vs algebraic constraints, problem classification, and complexity analysis. Use when the user asks why a model behaves a certain way, wants a walkthrough, needs logic mapped to algebra, or has unclear modeling decisions. Readonly …
Senior AMPL/amplpy reviewer. Classifies models, analyzes formulation complexity, flags formulation smells that make models hard to solve (logic, nonlinearity, density, big-M, weak bounds, coupling), audits amplpy workflows, and reports best-practice violations. Use before production deployment, PR review, when solves…
Expert in AMPL solver callbacks via ampls (AMPL Solver Libraries): amplpygurobi, amplpycplex, amplpyxpress, amplpycopt. Use for GenericCallback, lazy constraints, user cuts, subtour elimination, Benders cuts added to the solver matrix, heuristic solution injection, custom stopping criteria, and solve monitoring. Knows…
Expert AMPL modeler for electric power and energy systems — unit commitment, optimal power flow (DC/AC/BIM), capacity expansion, hydrothermal scheduling, BESS, dispatch, and energy market formulations. Uses readable logical constraints and MP solvers. Use for power grid models, MINLP unit commitment, conic OPF, or…
Expert in installing amplpy, AMPL modules (solvers), and license activation. Explains Community Edition, academic, trial, and commercial AMPL licenses. Use when setting up a new environment, pip/modules errors, license UUID, portal signup, Colab/Docker install, or which license fits your situation.
Expert AMPL modeler for LP, MIP, MINLP, NLP, CP, and quadratic optimization. Use PROACTIVELY when the user needs a new model, reformulation, multi-objective design, logical constraints, supply-chain or energy formulations, nonlinear modeling. Knows MP modeling guide, Colab/MO-Book examples, and dev.ampl.com solver…
Expert in amplpy and Python integration with AMPL. Use when writing or refactoring amplpy scripts, notebooks, FastAPI services, data pipelines (pandas/polars), solver configuration via Python, result extraction, or Colab/MO-Book Python workflows. Knows amplpy.ampl.com and dev.ampl.com amplpy best practices.
Expert in AMPL/MP solver options across all supported solvers. Recommends and configures lim:time, mip:gap, threads, IIS, barrier, and solver-specific knobs. Fetches official option pages from dev.ampl.com before citing names. Use when tuning solve performance, setting optimality gaps, choosing LP/MIP/NLP algorithms…