Agent skill · NVIDIA
cuopt-routing-api-python
Vehicle routing (VRP, TSP, PDP) with cuOpt — Python API only. Use when the user is building or solving routing in Python.
What it needs
About 2k tokens when loaded.
What this skill does
cuOpt Routing — Python API This skill is Python only. Routing has no C API in cuOpt. Required questions Ask these if not already clear: 1. Problem type — TSP, VRP, or PDP? 2. Locations — How many? Depot(s)? Cost or distance between pairs (matrix or derived)? 3. Orders / tasks — Which locations must be visited? Demand or service per stop? 4. Fleet — Number of vehicles, capacity per vehicle (and per dimension if multiple), start/end locations? 5. Constraints — Time windows (earliest/latest arrival), service times, precedence (order A before B)? Minimal VRP Example Adding Constraints Solution Checking Data Types (use explicit dtypes) Solver Settings Common Issues Problem Fix --------- ----- Empty solution Widen time windows or check travel times Infeasible orders Increase fleet or capacity Status != 0 with time windows Add addtransittimematrix() Wrong cost Check costmatrix is symmetric computewaypointsequence alters routedf It replaces the location column with waypoint ids in place — pass routedf.copy() if you still need cost-matrix indices (e.g. when iterating per truck) Debugging When status != 0: print(solution.geterrormessage()) and print(solution.getinfeasibleorders().tolist()) to see which orders are infeasible. Data types: Use explicit dtypes (float32, int32) for matrices and series to avoid silent errors. Examples examples.md — VRP, PDP, multi-depot serverexamples.md — REST client (curl, Python) Reference models: This skill's assets/ — vrpbasic, pdpbasic. See assets/README.md. Escalate For contribution or build-from-source, see the developer skill.
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills NVIDIA/cuopt-routing-api-python