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@@ -94,6 +94,7 @@ Run and optimize on AMD Instinct.
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|[`hyperloom-workload-optimizer`](https://github.com/amd/skills/blob/main/skills/hyperloom-workload-optimizer/SKILL.md)| Set up Hyperloom and autonomously optimize end-to-end LLM inference throughput on AMD Instinct GPUs, reporting a validated gain. |[Hyperloom](https://github.com/AMD-AGI/Hyperloom)|
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|[`magpie-kernel-evaluator`](https://github.com/amd/skills/blob/main/skills/magpie-kernel-evaluator/SKILL.md)| Evaluate GPU kernel correctness and performance, compare kernel implementations, and benchmark vLLM or SGLang inference with profiling, TraceLens, and torch-trace gap analysis. |[Magpie](https://github.com/AMD-AGI/Magpie)|
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|[`tracelens-analysis-orchestrator`](https://github.com/amd/skills/blob/main/skills/tracelens-analysis-orchestrator/SKILL.md)| Orchestrate modular PyTorch profiler trace analysis with TraceLens: generate perf reports, run system-level and compute-kernel subagents in parallel, and write a prioritized stakeholder report. |[TraceLens](https://github.com/AMD-AGI/TraceLens)|
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|[`rocprofiler-pc-sampling`](https://github.com/amd/skills/blob/main/skills/rocprofiler-pc-sampling/SKILL.md)| Profile a GPU application with rocprofv3 program counter (PC) sampling, then analyze the samples to surface hotspots and stall reasons. |[rocprofiler-sdk](https://github.com/ROCm/rocm-systems/tree/develop/projects/rocprofiler-sdk)|
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