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Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/alibaba/atrex-kernel-agent.Loading the repository README…
Showing 18 of 18 collected skills.
Use the agate CLI to submit GPU operator evaluations, compilation checks, profiling, disassembly and controlled development commands to atrex-gpu-gateway, and query environments and asynchronous results. Covers CUDA solution.json configuration and AKA…
Run Kernel evaluation, ABBA comparison, profiling and GPU probes through the session's Supervisor HTTP Runtime.
Query GPU optimization knowledge and hardware facts through the session's Supervisor Runtime.
Record research Directions and Experiments, query saved evidence, and submit a validated Episode Report through the Supervisor.
Let AKA autonomously add, run, inspect, and revise intra-kernel timeline probes for standalone CUDA/inline PTX or CuTe DSL when ordinary benchmark, NSYS, or NCU evidence cannot answer a specific kernel-internal timing question.
Choose and run ACU-only, adaptive PPU in-kernel timeline, or optional bounded joint analysis for a PPU kernel. Use for device-level bottleneck diagnosis, kernel-internal critical-path questions, or evidence that genuinely needs both; do not require all three…
Query saved measurement evidence and submit an Episode Report without Direction or Experiment recording.
Analyze GPU microarchitecture questions across vendors using focused microkernels, ISA inspection, and controlled A/B experiments when compiler behavior, layout, dependencies, or performance are unclear.
Run the evidence loop of one long-horizon GPU kernel optimization episode. Use this skill to reconstruct the incumbent, profile and localize a bottleneck, research progressively, plan one coherent direction, implement and repair, validate development…
Use the selected reliable GPU executor from the legacy Workflow.
Prepare requests for the selected AKA Execution entry point, consult Gateway or SSH guidance, and preserve complete execution output and artifacts. Use for handing prepared GPU commands, evaluation, or profiling work to AKA Execution; experiment planning and…
Let AKA autonomously add, run, inspect, and revise intra-kernel timeline probes for standalone CUDA/inline PTX or CuTe DSL when ordinary benchmark, NSYS, or NCU evidence cannot answer a specific kernel-internal timing question.
Choose and run ACU-only, adaptive PPU in-kernel timeline, or optional bounded joint analysis for a PPU kernel. Use for device-level bottleneck diagnosis, kernel-internal critical-path questions, or evidence that genuinely needs both; do not require all three…
Generate a structured implementation plan from an evidence draft. Validate paths, obtain configured independent Codex and Qoder reviews, synthesize available advice against repository evidence, preserve the draft, and produce testable acceptance criteria and…
Learn the target framework from enabled knowledge tools and implement a baseline GPU kernel. Use this skill to understand compute semantics, determine the target platform and framework, search reference implementations, and produce a correct V0 baseline with…
Mine a per-kernel optimization trace — a git repository capturing successive versions of one kernel being optimized — into structured, gate-validated optimization-experience records for the GPU kernel wiki. Use when asked to distill an optimization run, a…
Quickly extract a typed GPU-Wiki query intent from prose. Never inspect or query a knowledge store.
Mine AI coding-agent session transcripts into structured, gate-validated GPU-kernel optimization records for the wiki. Use when asked to turn vibe-coding sessions, Codex rollout logs, or Claude Code project transcripts into wiki records; to summarise what a…
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