A specialized AI agent model optimized for security and safety tasks, available in multiple GGUF quantization formats for efficient local deployment.
A quantized security-focused AI agent model based on Qwen3-4B, optimized for safety and security tasks. This skill provides guidance on deploying and using the AgentDoG-FG-Qwen3-4B model in GGUF format for local, privacy-preserving AI operations.
This skill helps you select, download, and deploy the appropriate quantization of the AgentDoG-FG-Qwen3-4B model for security and safety-related AI agent tasks. The model is available in multiple GGUF quantization levels, allowing you to balance quality, speed, and resource requirements based on your specific needs.
When a user requests assistance with the AgentDoG security model or asks about local security-focused AI deployment:
1. **Assess Requirements**: Determine the user's hardware constraints, quality needs, and use case specificity.
2. **Recommend Quantization Level**:
- For most users: Recommend **Q4_K_M** (2.8GB) as the optimal balance of quality, speed, and size
- For limited resources: Recommend **IQ3_S** (2.2GB) which beats Q3_K variants
- For maximum quality: Recommend **Q6_K** (3.7GB) for near-original quality
- For extreme resource constraints: Recommend **IQ2_S** or **IQ2_M** (1.7-1.8GB)
- For minimal viable deployment: **IQ1_M** (1.4GB) but warn about quality degradation
3. **Provide Download Instructions**:
```bash
# Example for Q4_K_M (recommended)
wget https://huggingface.co/mradermacher/AgentDoG-FG-Qwen3-4B-i1-GGUF/resolve/main/AgentDoG-FG-Qwen3-4B.i1-Q4_K_M.gguf
```
4. **Explain Usage**:
- Guide users to use llama.cpp, ollama, or other GGUF-compatible inference engines
- Explain the model is specifically trained for security and safety tasks
- Note the model is based on Qwen3-4B with Apache 2.0 license
- Emphasize privacy benefits of local deployment
5. **Quality Guidance**:
- IQ (Importance Matrix) quants generally provide better quality than standard quants at similar sizes
- Higher numbers (Q6 > Q5 > Q4) indicate higher quality but larger file size
- Reference the quantization comparison graph for quality/size tradeoffs
6. **Security Use Cases**:
- Vulnerability assessment assistance
- Security policy analysis
- Threat modeling support
- Safety-critical system evaluation
- Offline security research (no data leaves local machine)
**User**: "I need a local AI model for security analysis on a laptop with 8GB RAM"
**Response**: "I recommend the AgentDoG-FG-Qwen3-4B model in Q4_K_M quantization (2.8GB). This provides excellent quality while fitting comfortably in your RAM budget. Download with: `wget https://huggingface.co/mradermacher/AgentDoG-FG-Qwen3-4B-i1-GGUF/resolve/main/AgentDoG-FG-Qwen3-4B.i1-Q4_K_M.gguf` and run with llama.cpp or ollama for privacy-preserving security analysis."
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# Download SKILL.md from killerskills.ai/api/skills/agentdog-security-agent-gguf/raw