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@@ -86,6 +86,7 @@ Run and optimize on AMD Instinct.
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 | [`serving-llms-on-instinct`](skills/serving-llms-on-instinct/SKILL.md) | Deploy LLM inference on AMD Instinct GPUs end-to-end: detect hardware (or onboard via AMD Developer Cloud), validate model fit, apply the right vLLM recipe, and launch a benchmarked endpoint. SGLang and engine/backend selection in later phases. | in-repo |
 | [`llm-kernel-evaluator` (`magpie`)](skills/magpie/SKILL.md) | Evaluate GPU kernel correctness and performance, compare kernel implementations, and benchmark vLLM / SGLang inference with profiling, TraceLens, and torch-trace gap analysis. | [Magpie](https://github.com/AMD-AGI/Magpie) |
+| [`analysis-orchestrator (TraceLens)`](skills/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) |
 
 
 ## A federated catalog