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This is a legitimate scientific documentation skill for ESM protein language models. All findings are false positives: backticks are markdown formatting, eval() is PyTorch's model.eval() method, and the network+credentials+code pattern is expected for an API client. No malicious code, no credential harvesting, no suspicious system operations.

This is a legitimate scientific documentation skill for ESM protein language models. All findings are false positives: backticks are markdown formatting, eval() is PyTorch's model.eval() method, and the network+credentials+code pattern is expected for an API client. No malicious code, no credential harvesting, no suspicious system operations.

This is a legitimate scientific skill providing documentation for protein language models (ESM3 and ESM C). All content consists of documentation and Python examples using the official ESM SDK. Network endpoints reference only the official Forge API (forge.evolutionaryscale.ai) and HuggingFace for model weights. No executable scripts, no credential harvesting, no suspicious system operations.

This is a legitimate scientific skill providing documentation for protein language models (ESM3 and ESM C). All content consists of documentation and Python examples using the official ESM SDK. Network endpoints reference only the official Forge API (forge.evolutionaryscale.ai) and HuggingFace for model weights. No executable scripts, no credential harvesting, no suspicious system operations.

This is a legitimate scientific skill providing documentation for protein language models (ESM3 and ESM C). All content consists of documentation and Python examples using the official ESM SDK. Network endpoints reference only the official Forge API (forge.evolutionaryscale.ai) and HuggingFace for model weights. No executable scripts, no credential harvesting, no suspicious system operations.