NVIDIA · ramakrishnap-nv · Jun 26, 2026 · Jun 26, 2026 · Jun 26, 2026
@@ -7,7 +7,7 @@ This benchmark summarizes 3-Tier Evaluation from NVSkills-Eval results for the s
 ## Evaluation Summary
 
 - Skill: `cuopt-numerical-optimization-api-c`
-- Evaluation date: 2026-06-10
+- Evaluation date: 2026-06-26
 - NVSkills-Eval profile: `external`
 - Environment: `astra-sandbox`
 - Dataset: 4 evaluation tasks
@@ -55,33 +55,25 @@ Task composition is derived from the evaluation dataset when possible. Entries w
 | Dimension | Num | `claude-code` | `codex` |
 |---|---:|---:|---:|
 | Security | 4 | 100% (+0%) | 100% (+0%) |
-| Correctness | 4 | 88% (+16%) | 72% (+16%) |
-| Discoverability | 4 | 68% (+46%) | 55% (+36%) |
-| Effectiveness | 4 | 92% (+7%) | 70% (+17%) |
-| Efficiency | 4 | 66% (+48%) | 62% (+35%) |
+| Correctness | 4 | 88% (+31%) | 82% (+23%) |
+| Discoverability | 4 | 70% (+52%) | 63% (+45%) |
+| Effectiveness | 4 | 94% (+35%) | 94% (+33%) |
+| Efficiency | 4 | 69% (+44%) | 69% (+42%) |
 
 Score values show skill-assisted performance. Values in parentheses show uplift versus the no-skill baseline when baseline data is available.
 
 ## Tier 1: Static Validation Summary
 
-Tier 1 validation passed with observations. NVSkills-Eval ran 9 checks and found 7 total findings.
+Tier 1 validation passed with observations. NVSkills-Eval ran 1 checks and found 2 total findings.
 
 Top findings:
 
-- MEDIUM QUALITY/quality_efficiency: Deeply nested references in examples.md (`skills/cuopt-numerical-optimization-api-c/SKILL.md`)
 - MEDIUM SCHEMA/body_recommended_section: Missing recommended section: '## Instructions' (`skills/cuopt-numerical-optimization-api-c/SKILL.md`)
-- LOW QUALITY/quality_discoverability: No '## Purpose' section (`skills/cuopt-numerical-optimization-api-c/SKILL.md`)
-- LOW QUALITY/quality_reliability: No prerequisites/requirements documented (`skills/cuopt-numerical-optimization-api-c/SKILL.md`)
-- LOW QUALITY/quality_reliability: No limitations documented (`skills/cuopt-numerical-optimization-api-c/SKILL.md`)
+- LOW SCHEMA/author_format: Author must be of the form 'Name <email@host>' (`skills/cuopt-numerical-optimization-api-c/SKILL.md`)
 
 ## Tier 2: Deduplication Summary
 
-Tier 2 validation passed. NVSkills-Eval ran 2 checks and found 0 total findings.
-
-Notable observations:
-
-- Context Deduplication: Collected 9 file(s)
-- Inter-Skill Deduplication: Parsed skill 'cuopt-numerical-optimization-api-c': 105 char description
+This tier was not run or did not produce findings in this report.
 
 ## Publication Recommendation
 

@@ -14,6 +14,7 @@ metadata:
 ---
 
 
+
 # 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.

@@ -7,26 +7,32 @@ This skill is ready for commercial/non-commercial use. <br>
 NVIDIA <br>
 
 ### License/Terms of Use: <br>
-Apache 2.0 <br>
+Apache-2.0 <br>
 ## Use Case: <br>
-Developers and engineers embedding LP, MILP, or QP numerical optimization into C/C++ applications using the NVIDIA cuOpt GPU-accelerated solver. <br>
+Developers and engineers embedding LP, MILP, or QP optimization in C/C++ applications using the cuOpt GPU-accelerated solver. <br>
 
 ### Deployment Geography for Use: <br>
 Global <br>
 
+## Requirements / Dependencies: <br>
+**Requires API Key or External Credential:** [No] <br>
+**Credential Type(s):** [None] <br>  
+
+Do not include secrets in prompts/logs/output; use least-privilege credentials; rotate keys as appropriate. <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>
 - [C API Examples (LP/MILP)](references/examples.md) <br>
+- [Assets — Reference C Examples](assets/README.md) <br>
 - [cuOpt User Guide](https://docs.nvidia.com/cuopt/user-guide/latest/introduction.html) <br>
-- [cuOpt Examples Repository](https://github.com/NVIDIA/cuopt-examples) <br>
 
 
 ## Skill Output: <br>
 **Output Type(s):** [Code, Shell commands] <br>
-**Output Format:** [Markdown with inline C code blocks] <br>
+**Output Format:** [C source code with inline shell build commands] <br>
 **Output Parameters:** [1D] <br>
 **Other Properties Related to Output:** [None] <br>
 
@@ -37,7 +43,7 @@ Mitigation: Review and scan skill before deployment. <br>
 
 
 ## Evaluation Tasks: <br>
-Evaluated against 4 internal evaluation tasks (positive skill-activation cases) via NVSkills-Eval with the external profile. <br>
+Evaluated against 4 internal evaluation tasks (NVSkills-Eval, external profile, astra-sandbox environment). <br>
 
 ## Evaluation Metrics Used: <br>
 Reported benchmark dimensions: <br>
@@ -62,10 +68,10 @@ Underlying evaluation signals used in this run: <br>
 | Dimension | Num | `claude-code` | `codex` |
 |---|---:|---:|---:|
 | Security | 4 | 100% (+0%) | 100% (+0%) |
-| Correctness | 4 | 88% (+16%) | 72% (+16%) |
-| Discoverability | 4 | 68% (+46%) | 55% (+36%) |
-| Effectiveness | 4 | 92% (+7%) | 70% (+17%) |
-| Efficiency | 4 | 66% (+48%) | 62% (+35%) |
+| Correctness | 4 | 88% (+31%) | 82% (+23%) |
+| Discoverability | 4 | 70% (+52%) | 63% (+45%) |
+| Effectiveness | 4 | 94% (+35%) | 94% (+33%) |
+| Efficiency | 4 | 69% (+44%) | 69% (+42%) |
 
 ## Skill Version(s): <br>
 26.08.00 (source: frontmatter) <br>
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Expand Up		@@ -14,6 +14,7 @@ metadata:
		---



		# 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.
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