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This is a legitimate multi-objective optimization documentation skill. All 315 static findings are false positives. The scanner misinterpreted markdown code formatting backticks as shell commands, optimization algorithm names (NSGA-II, NSGA-III) as cryptographic algorithms, and optimization terminology as security threats. Python scripts contain standard pymoo optimization examples with no malicious code.

This is a legitimate multi-objective optimization documentation skill. All 315 static findings are false positives. The scanner misinterpreted markdown code formatting backticks as shell commands, optimization algorithm names (NSGA-II, NSGA-III) as cryptographic algorithms, and optimization terminology as security threats. Python scripts contain standard pymoo optimization examples with no malicious code.

All static analysis findings are false positives. The 'external_commands' findings are markdown backticks in documentation, not shell execution. No actual security risks detected in this optimization framework documentation.

This is a legitimate documentation and example-based skill for the pymoo optimization library. All code performs pure mathematical computations using numpy and matplotlib without any network calls, credential access, or file system manipulation beyond its own directory.