flydsl-kernel-authoring

flydsl-kernel-authoring is a skill for Claude Code, Codex from wenyi-li/awesome-agent-kernel-skills. It costs 236 tokens per session (8,588 once invoked), scanned A, original, no licence file.

A guide to FlyDSL, a Python language for writing custom AMD GPU kernels with MLIR-based compilation and explicit data-layout rules.

In plain words
What is it for?
Use it to author kernels for operations such as RMSNorm, LayerNorm, softmax, or fused normalization and residual-add chains.
Why use it?
It supports specialized GPU kernel work when profiling shows that a reduction or fused operation is a performance hotspot.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Use it to author kernels for operations such as RMSNorm, LayerNorm, softmax, or fused normalization and residual-add chains.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/wenyi-li/awesome-agent-kernel-skills/flydsl-kernel-authoring
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add wenyi-li/awesome-agent-kernel-skills --skill flydsl-kernel-authoring
Clone the repo
git clone --depth 1 https://github.com/wenyi-li/awesome-agent-kernel-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for flydsl-kernel-authoring

README.md
[![agentmods](https://agentmods.dev/badge/skills/wenyi-li/awesome-agent-kernel-skills/flydsl-kernel-authoring/github.svg)](https://agentmods.dev/skills/wenyi-li/awesome-agent-kernel-skills/flydsl-kernel-authoring)
Your own site
<a href="https://agentmods.dev/skills/wenyi-li/awesome-agent-kernel-skills/flydsl-kernel-authoring"><img src="https://agentmods.dev/badge/skills/wenyi-li/awesome-agent-kernel-skills/flydsl-kernel-authoring/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for flydsl-kernel-authoring

Your own site · 80×15
<a href="https://agentmods.dev/skills/wenyi-li/awesome-agent-kernel-skills/flydsl-kernel-authoring"><img src="https://agentmods.dev/badge/skills/wenyi-li/awesome-agent-kernel-skills/flydsl-kernel-authoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 236 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 8,588 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00236 $0.08588
Opus 5 $0.00118 $0.04294
Sonnet 5 $0.00047 $0.01718
Haiku 4.5 $0.00024 $0.00859

Measured 10d ago against content hash 186ccf57d653, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

flydsl-kernel-authoring scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

flydsl-kernel-authoring/SKILL.md · 686 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 686 lines · 236 tokens per session scan A 186ccf57d653

Subscribe to this mod's changes

flydsl-kernel-authoring is a skill published in the GitHub repository wenyi-li/awesome-agent-kernel-skills (9 stars, last pushed 3mo ago), with no licence file. It adds 236 tokens to every session and 8,588 once invoked, about $0.0012 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

pytorch-patterns

PyTorch deep learning patterns and best practices for building robust, efficient, and reproducible training pipelines, model architectures, and data loading.

affaan-m/ECC · 32 tokens

accelerate

Run PyTorch training across GPUs with minimal changes.

NousResearch/hermes-agent · 13 tokens

developing-genkit-python

Develop AI-powered applications using Genkit in Python. Use when the user asks about Genkit, AI agents, flows, or tools in Python, or when encountering Genkit errors, import issues, or API problems.

google/skills · 49 tokens

optimize-for-gpu

GPU-accelerates scientific Python on NVIDIA hardware and verifies that the result is correct and faster. Use for CUDA/GPU optimization; CPU-bound NumPy, SciPy, pandas, scikit-learn, NetworkX, scikit-image, vector-search, image-processing, graph, simulation, or file-I/O workloads; CuPy, cuDF, cuML, cuGraph, cuVS…

K-Dense-AI/scientific-agent-skills · 151 tokens

marimo-pair

Work inside the user's live marimo notebook from the code editor: run Python in the same kernel the user does, inspect live notebook state, and commit durable notebook changes through code mode. Use whenever you create, analyze, or improve the user's marimo notebook.

marimo-team/marimo · 57 tokens

minicpm5-deploy-transformers

Run MiniCPM5-1B or MiniCPM5-2B with Hugging Face Transformers for one-shot Python generation on GPU (bfloat16) or CPU (float32). Use when the user wants a quick Python script, no server, no extra deps, or asks for "Transformers", "AutoModelForCausalLM", "model.generate" with MiniCPM5.

OpenBMB/MiniCPM · 90 tokens