How do I install the Kebab Gemm Config Tuning skill?

Run npx skillmds@latest add tomevault-io/kebab-gemm-config-tuning in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Kebab Gemm Config Tuning safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Kebab Gemm Config Tuning?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Kebab Gemm Config Tuning free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Kebab Gemm Config Tuning?

tomevault-io (@tomevault-io) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Kebab Gemm Config Tuning by tomevault-io

Name: Kebab Gemm Config Tuning
Author: tomevault-io

Kebab Gemm Config Tuning

Tune GEMM experiment settings in Kebab using config.yaml and optimization docs. Use when asked to adjust matrix sizes, precision, layout modes, tile sizes, kernel versions, or to design reproducible performance experiments. Use when this capability is needed.

tomevault-io Updated Sep 17, 2026

File contents

Kebab GEMM Config Tuning

When to Use This Skill

User asks to change GEMM benchmark parameters
User asks to compare layout modes (RR, RC, CR, CC)
User asks to test precision (float16, bfloat16, float32) or kernel version lists
User asks for tile-size and occupancy-oriented tuning plans

Key Configuration Surface

Main file: config.yaml

Important keys under operators.gemm:

impl
versions
matrix_sizes
modes
precisions
tile_sizes
init_method

Step-by-Step Workflow

Edit config.yaml with one controlled change at a time.
Build and run benchmark:
- make build
- make bench-gemm
For deeper analysis, run:
- make tune-gemm-cute (or cuda/ref)
Save and compare outputs from bench_results/, profiling/, and reports/.

Tuning Rules from Repository Context

Hopper/WGMMA paths generally expect sm_90a.
The documented tile constraint notes K dimension compatibility requirements for GMMA pathways.
Keep experiment dimensions and precision explicit to ensure reproducibility.

Troubleshooting

Issue	Mitigation
Unexpected perf regression	Revert to previous `versions`/`tile_sizes` baseline and isolate one variable
Precision mismatch	Verify selected kernel path supports requested precision
Layout-specific anomaly	Test all `modes` and compare independently

References

config.yaml
docs/optimization_plan.md
docs/TILE_SIZE_CONFIGURATION.md
Makefile GEMM benchmark/profile targets

Converted and distributed by TomeVault — claim your Tome and manage your conversions.

---name: kebab-gemm-config-tuningdescription: Tune GEMM experiment settings in Kebab using config.yaml and optimization docs. Use when asked to adjust matrix sizes, precision, layout modes, tile sizes, kernel versions, or to design reproducible performance experiments. Use when this capability is needed.---# Kebab GEMM Config Tuning## When to Use This Skill- User asks to change GEMM benchmark parameters- User asks to compare layout modes (`RR`, `RC`, `CR`, `CC`)- User asks to test precision (`float16`, `bfloat16`, `float32`) or kernel version lists- User asks for tile-size and occupancy-oriented tuning plans## Key Configuration SurfaceMain file: `config.yaml`Important keys under `operators.gemm`:- `impl`- `versions`- `matrix_sizes`- `modes`- `precisions`- `tile_sizes`- `init_method`## Step-by-Step Workflow1. Edit `config.yaml` with one controlled change at a time.2. Build and run benchmark: - `make build` - `make bench-gemm`3. For deeper analysis, run: - `make tune-gemm-cute` (or cuda/ref)4. Save and compare outputs from `bench_results/`, `profiling/`, and `reports/`.## Tuning Rules from Repository Context- Hopper/WGMMA paths generally expect `sm_90a`.- The documented tile constraint notes K dimension compatibility requirements for GMMA pathways.- Keep experiment dimensions and precision explicit to ensure reproducibility.## Troubleshooting| Issue | Mitigation ||---|---|| Unexpected perf regression | Revert to previous `versions`/`tile_sizes` baseline and isolate one variable || Precision mismatch | Verify selected kernel path supports requested precision || Layout-specific anomaly | Test all `modes` and compare independently |## References- `config.yaml`- `docs/optimization_plan.md`- `docs/TILE_SIZE_CONFIGURATION.md`- `Makefile` GEMM benchmark/profile targets---> Converted and distributed by [TomeVault](https://tomevault.io/claim/lancerlab) — claim your Tome and manage your conversions.

Frequently asked questions