[codex] chore: touch non-eval skills for nvcarps ci

skills/cuopt-numerical-optimization-api-c/SKILL.md

@@ -4,6 +4,7 @@ version: "26.06.00"
 description: LP, MILP, and QP (beta) with cuOpt — C API only. Use when the user is embedding LP, MILP, or QP in C/C++.
 ---
 
+
 # cuOpt Numerical Optimization — C API
 
 Solve LP, MILP, and QP problems via the cuOpt C API. The same library, headers, build pattern, and core calls (`cuOptCreate*Problem`, `cuOptSolve`, `cuOptGetObjectiveValue`) apply across all three; QP extends the API with quadratic-objective creation calls.

skills/cuopt-numerical-optimization-api-c/skill-card.md

@@ -0,0 +1,40 @@
+## Description: <br>
+LP, MILP, and QP (beta) with cuOpt — C API only. Use when the user is embedding LP, MILP, or QP in C/C++. <br>
+
+This skill is ready for commercial/non-commercial use. <br>
+
+## Owner: NVIDIA <br>
+
+### License/Terms of Use: <br>
+Apache 2.0 <br>
+## Use Case: <br>
+Developers and engineers embedding linear programming, mixed-integer linear programming, or quadratic programming solvers into C/C++ applications using the NVIDIA cuOpt C API. <br>
+
+### Deployment Geography for Use: <br>
+Global <br>
+
+## Known Risks and Mitigations: <br>
+Risk: Review before execution as proposals could introduce incorrect or misleading guidance into skills. <br>
+Mitigation: Review and scan skill before deployment. <br>
+
+## Reference(s): <br>
+- [cuOpt User Guide](https://docs.nvidia.com/cuopt/user-guide/latest/introduction.html) <br>
+- [cuOpt API Reference](https://docs.nvidia.com/cuopt/user-guide/latest/api.html) <br>
+- [cuOpt Examples Repository](https://github.com/NVIDIA/cuopt-examples) <br>
+- [C API Examples (resources/examples.md)](resources/examples.md) <br>
+
+
+## Skill Output: <br>
+**Output Type(s):** [Code, Shell commands, Configuration instructions] <br>
+**Output Format:** [Markdown with inline C code blocks] <br>
+**Output Parameters:** [1D] <br>
+**Other Properties Related to Output:** [None] <br>
+
+## Skill Version(s): <br>
+26.06.00 (source: frontmatter) <br>
+
+## Ethical Considerations: <br>
+NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal team to ensure this skill meets requirements for the relevant industry and use case and addresses unforeseen product misuse. <br>
+
+(For Release on NVIDIA Platforms Only) <br>
+Please report quality, risk, security vulnerabilities or NVIDIA AI Concerns [here](https://app.intigriti.com/programs/nvidia/nvidiavdp/detail). <br>

skills/cuopt-numerical-optimization-api-c/skill.oms.sig

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skills/cuopt-numerical-optimization-api-cli/SKILL.md

@@ -4,6 +4,7 @@ version: "26.06.00"
 description: LP, MILP, and QP (beta) with cuOpt — CLI only (MPS files, cuopt_cli). Use when the user is solving LP, MILP, or QP from MPS via command line.
 ---
 
+
 # cuOpt Numerical Optimization — CLI
 
 Solve LP, MILP, and QP problems from MPS files via `cuopt_cli`. The same command, options, and MPS workflow apply across all three; QP uses the standard MPS quadratic-objective extension.

skills/cuopt-numerical-optimization-api-cli/skill-card.md

@@ -0,0 +1,39 @@
+## Description: <br>
+LP, MILP, and QP (beta) with cuOpt — CLI only (MPS files, cuopt_cli). Use when the user is solving LP, MILP, or QP from MPS via command line. <br>
+
+This skill is ready for commercial/non-commercial use. <br>
+
+## Owner: NVIDIA <br>
+
+### License/Terms of Use: <br>
+Apache 2.0 <br>
+## Use Case: <br>
+Developers and engineers use this skill to solve linear programming (LP), mixed-integer linear programming (MILP), and quadratic programming (QP) problems from MPS files via the cuopt_cli command-line interface. <br>
+
+### Deployment Geography for Use: <br>
+Global <br>
+
+## Known Risks and Mitigations: <br>
+Risk: Review before execution as proposals could introduce incorrect or misleading guidance into skills. <br>
+Mitigation: Review and scan skill before deployment. <br>
+
+## Reference(s): <br>
+- [cuOpt User Guide](https://docs.nvidia.com/cuopt/user-guide/latest/introduction.html) <br>
+- [cuOpt API Reference](https://docs.nvidia.com/cuopt/user-guide/latest/api.html) <br>
+- [cuOpt Examples](https://github.com/NVIDIA/cuopt-examples) <br>
+
+
+## Skill Output: <br>
+**Output Type(s):** [Shell commands, Configuration instructions, Code] <br>
+**Output Format:** [Markdown with inline bash code blocks] <br>
+**Output Parameters:** [1D] <br>
+**Other Properties Related to Output:** [None] <br>
+
+## Skill Version(s): <br>
+26.06.00 (source: frontmatter) <br>
+
+## Ethical Considerations: <br>
+NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal team to ensure this skill meets requirements for the relevant industry and use case and addresses unforeseen product misuse. <br>
+
+(For Release on NVIDIA Platforms Only) <br>
+Please report quality, risk, security vulnerabilities or NVIDIA AI Concerns [here](https://app.intigriti.com/programs/nvidia/nvidiavdp/detail). <br>

skills/cuopt-numerical-optimization-api-cli/skill.oms.sig

@@ -0,0 +1 @@
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skills/cuopt-routing-api-python/SKILL.md

@@ -4,6 +4,7 @@ version: "26.06.00"
 description: Vehicle routing (VRP, TSP, PDP) with cuOpt — Python API only. Use when the user is building or solving routing in Python.
 ---
 
+
 # cuOpt Routing — Python API
 
 Confirm problem type (TSP, VRP, PDP) and data (locations, orders, fleet, constraints) before coding.