Guidance for AI coding assistants working in this repository.
Repository-specific workflow guides ("skills") live in .agents/skills/. Each subdirectory is a self-contained guide for a multi-stage workflow. Read the SKILL.md at the top of each subdirectory for an overview; the other files in that directory are referenced from SKILL.md and should be read on demand.
| Skill | What it does |
|---|---|
liger-kernel-dev |
Develops new Triton kernels from a PyTorch reference (or modifies existing kernels). 3-stage pipeline: Analyze → Generate → Validate. NVIDIA GPUs only. |
liger-autopatch |
Adds Liger Kernel support for a new HuggingFace Transformers model, or modifies an existing monkey-patch. 3-stage pipeline: Analyze → Generate → Validate. |
liger-kernel-perf |
Optimizes the performance of an existing Liger Triton kernel. 3-stage pipeline: Profile → Optimize → Finalize. NVIDIA GPUs only. |
The skills are written to be runtime-agnostic — they describe the workflow as a sequence of stages a competent agent (or human) can follow. Where a stage says "Follow the X workflow in x.md", that's a directive to read and execute that file's instructions; runtimes that support parallel subagents may delegate the stage, but it is not required.
For convenience, some assistants auto-discover skills from vendor-specific paths. These point at the canonical .agents/skills/ directory:
.claude/skills→ symlink →.agents/skills(for Claude Code)
If you're adding support for another assistant, add a symlink (or your tool's preferred adapter) pointing to .agents/skills/. Do not duplicate the content.
- Source layout:
src/liger_kernel/{ops,transformers}/for Triton ops andnn.Module/ HF wrappers respectively - Tests:
test/transformers/(unit) andtest/convergence/{bf16,fp32}/(model convergence) - Benchmarks:
benchmark/scripts/(scripts) andbenchmark/data/all_benchmark_data.csv(results) - Lint/format:
make checkstyle(usesruff) - Install dev mode:
pip install -e ".[dev]"
See README.md for the project overview and contribution guide.