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Add AICodeSlopMonitor and SynthScan to Tools section #5

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2 changes: 2 additions & 0 deletions README.md
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Expand Up @@ -61,6 +61,8 @@ If you find this list helpful, give it a ⭐ on GitHub, share it, and contribute
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## Tools 🛠️
- **[AICodeSlopMonitor](https://slopcodemonitor.ai/)**: Detects low-quality and AI-generated code patterns to help developers review and improve codebases.
- **[SynthScan](https://github.com/marcoramilli/SynthScan)**: Scans codebases for AI-generated code patterns.
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Copilot AI Apr 18, 2026

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These two entries focus on detecting AI-generated/low-quality code patterns, which doesn't clearly align with this repository's stated theme of AI efficiency (making AI systems faster/cheaper/smaller/greener). Please either (1) clarify the descriptions to explicitly connect them to efficiency (e.g., detecting inefficient AI-generated code that impacts performance/cost), or (2) move them into a more appropriate/new section (e.g., code review / reliability) to keep the list coherent.

Suggested change
- **[AICodeSlopMonitor](https://slopcodemonitor.ai/)**: Detects low-quality and AI-generated code patterns to help developers review and improve codebases.
- **[SynthScan](https://github.com/marcoramilli/SynthScan)**: Scans codebases for AI-generated code patterns.
- **[AICodeSlopMonitor](https://slopcodemonitor.ai/)**: Detects low-quality and AI-generated code patterns that may introduce inefficient implementations, helping developers reduce unnecessary compute, performance overhead, and maintenance cost.
- **[SynthScan](https://github.com/marcoramilli/SynthScan)**: Scans codebases for AI-generated code patterns that can be reviewed for inefficiencies affecting runtime performance, resource usage, and engineering cost.

Copilot uses AI. Check for mistakes.
- :heart: **[Pruna](https://docs.pruna.ai/en/latest/)** :heart:: A package to make AI models faster, smaller, faster, greener by combining compression methods (incl. quantization, pruning, caching, compilation, distillation...) on various hardware.
- **[TensorRT](https://developer.nvidia.com/tensorrt)**: High-performance deep learning inference library for NVIDIA GPUs.
- **[ONNX](https://onnx.ai/)**: Open Neural Network Exchange format for interoperability among deep learning frameworks.
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