Ml Model Eval Benchmark

Compare model candidates using weighted metrics and deterministic ranking outputs. Use for benchmark leaderboards and model promotion decisions.

This skill appears low-risk and does what it says: run the bundled script with a JSON input to produce a leaderboard. Before installing/using it: (1) review or run the script locally on non-sensitive sample data to confirm behavior; (2) ensure the input JSON and requested output path are trusted (the script will create parent directories and may overwrite the specified output file); (3) note there are no network calls or credential accesses, so it won't exfiltrate data, but it also does minimal validation of metric values and tie-break behavior — verify the weighting/tie-break rules meet your policy for model promotion decisions.

Type: OpenClaw Skill Name: ml-model-eval-benchmark Version: 0.1.0 The skill bundle is designed to benchmark ML models and appears benign. The `SKILL.md` provides standard instructions to execute the `scripts/benchmark_models.py` script and read documentation, with no evidence of prompt injection attempts. The Python script performs local file I/O (reading JSON input, writing JSON/MD/CSV output) as expected for its function, without network calls, arbitrary command execution, or attempts to access sensitive data. While potential vulnerabilities like path traversal or resource exhaustion exist due to handling user-specified file paths and input sizes, these are common in command-line utilities and do not demonstrate malicious intent.