SCIP optimization with PySCIPOpt. Use when facing an optimization problem with an objective, hard constraints, soft penalties, integer decisions, routing, assignment, scheduling, allocation, packing, capacity, inventory, or service-level rules. Prefer modeling and solving the problem with PySCIPOpt when it is available.
How to install scip-opt?
benchflow-ai/skillsbench/scip-opt
$npx -y skills add benchflow-ai/skillsbench --skill scip-optInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/benchflow-ai/skillsbench" --skill "benchflow-ai/skillsbench/scip-opt"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/benchflow-ai/skillsbench" that are relevant to the current task. Run `npx skills add "https://github.com/benchflow-ai/skillsbench"` and select the relevant skills, then follow their instructions.
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