Security audit
Security checks for vulnerabilities and agentic risk
This skill is a small, purpose-aligned Ollama tuning helper that reads a user-provided dataset and sends sample prompts to a local Ollama model, with no evidence of hidden persistence, exfiltration, or destructive behavior.
Before installing, confirm you have Ollama configured as intended and do not use datasets containing secrets, personal data, or proprietary text unless you are comfortable processing that data through your local Ollama setup. Expect some rough packaging: the documented command wrapper and prompts/system.md reference are not present in the artifact.
Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.
!ollama-model-tuner --model llama3 --dataset ./data.json --task classification
The script sends dataset-derived prompts directly to an external/local Ollama model service via ollama.chat without any notice, consent flow, or data-sensitivity checks. If the dataset contains proprietary, personal, or otherwise sensitive prompt content, this can cause unintended disclosure to another service boundary and create privacy/compliance issues.
No suspicious patterns detected.