evaluating-llms-harness
Pass
Audited by Gen Agent Trust Hub on Aug 28, 2026
Risk Level: SAFECOMMAND_EXECUTIONDYNAMIC_EXECUTION
Full Analysis
- [COMMAND_EXECUTION]: The skill documents the use of the lm_eval CLI for running standardized benchmarks like MMLU and GSM8K across different model backends.
- [DYNAMIC_EXECUTION]: Contains Python examples demonstrating the automation of evaluation workflows using os.system calls within training loops and checkpoint monitoring.
- [DYNAMIC_EXECUTION]: Explains how to use custom task configurations that leverage the !function YAML tag to dynamically load Python logic from local files for dataset preprocessing and scoring.
- [DYNAMIC_EXECUTION]: Explicitly references the --allow_code_execution parameter, a standard feature of the evaluation harness used to run model-generated code within a controlled environment for benchmarks such as HumanEval.
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