Agentic Incident Response Orchestrator Baseline Model
Model Description
This repository contains a small, transparent prototype model for Production teams need agentic automation without allowing an LLM-style planner to execute unsafe remediation.
The model combines per-label token weights with IDF-weighted evidence retrieval. It was generated for reproducible architecture demonstrations and does not call a hosted LLM.
Evaluation
- Held-out synthetic examples: 4
- Accuracy: 1
- Intended metrics: tool_routing_accuracy, unsafe_action_block_rate, plan_completion
Intended Use
- Architecture prototyping
- CI and evaluation examples
- Local baseline comparisons
- Educational experimentation
Hugging Face Task Coverage
text-classificationtext-generationsummarizationquestion-answering
Limitations and Risks
The generated agent uses simulated tools. Production integrations must enforce least privilege and human approval.
The dataset is synthetic and small. Do not use this model for consequential decisions without representative data, expert review, and production-grade evaluation.
Reproducibility
The linked GitHub repository includes train.py, the exact dataset split,
evaluation code, and the model JSON format.