add-gpu-op

# Skill: Add GPU Op ## When to use When the Core OpSpec agent has produced a new op spec and you need to implement GPU plugin support: kernel implementation, registration, and testing. ## Steps Execute in order — each step produces artifacts consumed by the next. | Step | File | Purpose | |---|---|---| | 0a | [step0-plan.md](step0-plan.md) | Read op spec, build implementation plan, decide kernel vs oneDNN path | | 0b | [step0-parse-spec.md](step0-parse-spec.md) | Parse op spec JSON/MD into GPU-readable format | | 1 | [step1-hardware-analysis.md](step1-hardware-analysis.md) | Identify hardware constraints, sub-group size, memory layout requirements | | 2 | [step2-file-structure.md](step2-file-structure.md) | Create kernel and primitive files, register in factory | | 3a | [step3-kernel-development.md](step3-kernel-development.md) | Write OpenCL kernel (blocked reads, sub-groups, LWS tuning) | | 3b | [step3-write-tests.md](step3-write-tests.md) | Write layer tests | | 3c | [step3-run-tests.md](step3-run-tests.md) | Run and verify tests | | 3d | [step3-profiling.md](step3-profiling.md) | Profile and tune kernel | | 4 | [step4-onednn-integration.md](step4-onednn-integration.md) | Add oneDNN-backed primitive path where applicable | | 5 | [step5-optimize.md](step5-optimize.md) | Final performance optimizations | ## Entry point for orchestrated use When invoked by the GPU Agent or Enable Operator Agent, start from [orchestrator.md](orchestrator.md) — it selects the relevant subset of steps based on the op type and available hardware.