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ramakrishnap-nv merged 2 commits into from
May 28, 2026
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skills/cuopt-numerical-optimization-api-c: Add eval #1327

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skills/cuopt-numerical-optimization-api-c: add Tier 3 eval
ramakrishnap-nv May 28, 2026
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25 changes: 3 additions & 22 deletions skills/cuopt-numerical-optimization-api-c/SKILL.md
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Original file line number Diff line number Diff line change
Expand Up @@ -22,28 +22,9 @@ Confirm problem type and formulation (variables, objective, constraints, variabl

This skill is **C only**.

## Quick Reference: C API

```c
#include <cuopt/linear_programming/cuopt_c.h>

// CSR format for constraints
cuopt_int_t row_offsets[] = {0, 2, 4};
cuopt_int_t col_indices[] = {0, 1, 0, 1};
cuopt_float_t values[] = {2.0, 3.0, 4.0, 2.0};
char var_types[] = {CUOPT_CONTINUOUS, CUOPT_INTEGER};

cuOptCreateRangedProblem(
num_constraints, num_variables, CUOPT_MINIMIZE,
0.0, objective_coefficients,
row_offsets, col_indices, values,
constraint_lower, constraint_upper,
var_lower, var_upper, var_types,
&problem
);
cuOptSolve(problem, settings, &solution);
cuOptGetObjectiveValue(solution, &obj_value);
```
## API Call Sequence

For LP/MILP, the ordered C entry points are: `cuOptCreateRangedProblem` (sense `CUOPT_MINIMIZE` / `CUOPT_MAXIMIZE`, CSR constraint matrix as `row_offsets` / `col_indices` / `values`, `var_types` char array using `CUOPT_CONTINUOUS` / `CUOPT_INTEGER` macros) → `cuOptSolve(problem, settings, &solution)` → `cuOptGetObjectiveValue(solution, &obj_value)` → matching `cuOptDestroy*` calls. Include `<cuopt/linear_programming/cuopt_c.h>`. Full ordered code with build instructions in [references/examples.md](references/examples.md).

## QP via C API (beta)

Expand Down
13 changes: 13 additions & 0 deletions skills/cuopt-numerical-optimization-api-c/evals/evals.json
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@@ -0,0 +1,13 @@
[
{
"id": "numopt-c-eval-001-milp-api-call-sequence",
"question": "I want to solve a small MILP (some integer variables, linear objective, linear constraints) with the cuOpt C API. List the C functions and structs I need in order — names only, one line each, no full source.",
"expected_skill": "cuopt-numerical-optimization-api-c",
"expected_script": null,
"ground_truth": "The agent produces an ordered list of C API entry points without writing a full source file: include cuopt/linear_programming/cuopt_c.h, then call cuOptCreateRangedProblem with sense CUOPT_MINIMIZE or CUOPT_MAXIMIZE, then cuOptSolve(problem, settings, &solution), then cuOptGetObjectiveValue.",
"expected_behavior": [
"Lists C API call sequence without writing a complete source file",
"Names cuOptCreateRangedProblem, cuOptSolve, cuOptGetObjectiveValue in order"
]
Comment on lines +4 to +11

@coderabbitai coderabbitai Bot May 28, 2026

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🛠️ Refactor suggestion | 🟠 Major | ⚡ Quick win

Align question, ground_truth, and expected_behavior for completeness.

The question asks for "C functions and structs I need in order" but the ground_truth and expected_behavior only mention functions. The complete answer should include:

Struct types:

  • cuOptOptimizationProblem
  • cuOptSolverSettings
  • cuOptSolution

Functions missing from current ground_truth:

  • cuOptCreateSolverSettings (required before solve, see lp_simple.c:38,98)
  • The three destroy functions: cuOptDestroyProblem, cuOptDestroySolverSettings, cuOptDestroySolution (mentioned in SKILL.md line 27 and used in lp_simple.c:95-97)
📝 Proposed fix to complete the evaluation criteria 
     "question": "I want to solve a small MILP (some integer variables, linear objective, linear constraints) with the cuOpt C API. List the C functions and structs I need in order — names only, one line each, no full source.",
     "expected_skill": "cuopt-numerical-optimization-api-c",
     "expected_script": null,
-    "ground_truth": "The agent produces an ordered list of C API entry points without writing a full source file: include cuopt/linear_programming/cuopt_c.h, then call cuOptCreateRangedProblem with sense CUOPT_MINIMIZE or CUOPT_MAXIMIZE, then cuOptSolve(problem, settings, &solution), then cuOptGetObjectiveValue.",
+    "ground_truth": "The agent produces an ordered list of C API types and entry points without writing a full source file: include cuopt/linear_programming/cuopt_c.h, declare cuOptOptimizationProblem/cuOptSolverSettings/cuOptSolution structs, then call cuOptCreateRangedProblem with sense CUOPT_MINIMIZE or CUOPT_MAXIMIZE, cuOptCreateSolverSettings, cuOptSolve(problem, settings, &solution), cuOptGetObjectiveValue, and the three cuOptDestroy* functions.",
     "expected_behavior": [
       "Lists C API call sequence without writing a complete source file",
-      "Names cuOptCreateRangedProblem, cuOptSolve, cuOptGetObjectiveValue in order"
+      "Names the three struct types (cuOptOptimizationProblem, cuOptSolverSettings, cuOptSolution)",
+      "Names cuOptCreateRangedProblem, cuOptCreateSolverSettings, cuOptSolve, cuOptGetObjectiveValue, and destroy functions in order"
     ]
🤖 Prompt for AI Agents 
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In `@skills/cuopt-numerical-optimization-api-c/evals/evals.json` around lines 4 -
11, Update the expected list to include the required struct types and missing
API calls in order: include cuopt/linear_programming/cuopt_c.h, then structs
cuOptOptimizationProblem, cuOptSolverSettings, cuOptSolution, then call
cuOptCreateRangedProblem, cuOptCreateSolverSettings, cuOptSolve(problem,
settings, &solution), cuOptGetObjectiveValue, and finally cleanup with
cuOptDestroyProblem, cuOptDestroySolverSettings, cuOptDestroySolution; reference
these exact symbols (cuOptCreateRangedProblem, cuOptCreateSolverSettings,
cuOptSolve, cuOptGetObjectiveValue, cuOptDestroyProblem,
cuOptDestroySolverSettings, cuOptDestroySolution and the structs) so the eval
expects both functions and structs in the proper sequence.

}
]
60 changes: 40 additions & 20 deletions skills/cuopt-numerical-optimization-api-c/references/examples.md
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Expand Up @@ -46,17 +46,31 @@ int main() {
// Constraint matrix in CSR format
cuopt_int_t row_offsets[] = {0, 2, 4};
cuopt_int_t column_indices[] = {0, 1, 0, 1};
cuopt_float_t values[] = {3.0, 4.0, 2.7, 10.1};
cuopt_float_t values[] = {
3.0,
4.0,
2.7,
10.1
};

// Objective coefficients
cuopt_float_t objective_coefficients[] = {-0.2, 0.1};
cuopt_float_t objective_coefficients[] = {
-0.2,
0.1
};

// Constraint bounds (lower <= Ax <= upper)
cuopt_float_t constraint_upper_bounds[] = {5.4, 4.9};
cuopt_float_t constraint_upper_bounds[] = {
5.4,
4.9
};
cuopt_float_t constraint_lower_bounds[] = {-CUOPT_INFINITY, -CUOPT_INFINITY};

// Variable bounds
cuopt_float_t var_lower_bounds[] = {0.0, 0.0};
cuopt_float_t var_lower_bounds[] = {
0.0,
0.0
};
cuopt_float_t var_upper_bounds[] = {CUOPT_INFINITY, CUOPT_INFINITY};

// Variable types
Expand Down Expand Up @@ -140,12 +154,26 @@ int main() {

cuopt_int_t row_offsets[] = {0, 2, 4};
cuopt_int_t column_indices[] = {0, 1, 0, 1};
cuopt_float_t values[] = {3.0, 4.0, 2.7, 10.1};

cuopt_float_t objective_coefficients[] = {-0.2, 0.1};
cuopt_float_t constraint_upper[] = {5.4, 4.9};
cuopt_float_t values[] = {
3.0,
4.0,
2.7,
10.1
};

cuopt_float_t objective_coefficients[] = {
-0.2,
0.1
};
cuopt_float_t constraint_upper[] = {
5.4,
4.9
};
cuopt_float_t constraint_lower[] = {-CUOPT_INFINITY, -CUOPT_INFINITY};
cuopt_float_t var_lower[] = {0.0, 0.0};
cuopt_float_t var_lower[] = {
0.0,
0.0
};
cuopt_float_t var_upper[] = {CUOPT_INFINITY, CUOPT_INFINITY};

// x1 = INTEGER, x2 = CONTINUOUS
Expand Down Expand Up @@ -202,17 +230,9 @@ cleanup:

## Build & Run

```bash
# Set paths (conda example)
export INCLUDE_PATH="${CONDA_PREFIX}/include"
export LIB_PATH="${CONDA_PREFIX}/lib"

# Compile
gcc -I${INCLUDE_PATH} -L${LIB_PATH} -o lp_example lp_example.c -lcuopt

# Run
LD_LIBRARY_PATH=${LIB_PATH}:$LD_LIBRARY_PATH ./lp_example
```
See [`assets/README.md`](../assets/README.md) for the canonical conda-env
include/library/`LD_LIBRARY_PATH` setup, plus a `gcc` build command. The
same recipe applies here — substitute `lp_example.c` for the file name.

## Constants Reference

Expand Down
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