AMD Skills
Official AMD skills teach an agent to set up ROCm, serve LLMs on Instinct and EPYC, profile GPUs and quantize models.
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- Last commit
- MIT
Extended access
Why this level
- Skills run driver installs, containers and scripts on a GPU machine.
- Optimization on real hardware changes system configuration.
Install
- Works in
In your terminal, with SkillFoxx CLI
npx skillfoxx add skills/amd-skillsDetects the agents on your machine, shows the access level and pins the version.
Other ways to install
Access and checks
How we reviewExtended accessThe tool runs code or makes network calls and only reads external data.
- Skills run driver installs, containers and scripts on a GPU machine.
- Optimization on real hardware changes system configuration.
This is third-party code. Review the repository files before installing.
What it does
AMD Skills is a catalog of Agent Skills describing the working path through the AMD software stack. Each `skills/` folder holds a `SKILL.md`, a `skill-card.md` with the owner and license, and sometimes scripts and references. The catalog has three areas: client (Ryzen AI and Lemonade), cross-stack (ROCm diagnostics, AMD Quark quantization) and server (inference on AMD Instinct and EPYC, rocprofiler and TraceLens profiling, FlyDSL kernels). The skills work in Cursor, Claude Code, Codex and Gemini CLI.
Who it is for. Developers on ROCm, Ryzen AI and AMD Instinct who want an agent's help bringing up inference or tracing a GPU failure.
Good fit when
- PyTorch `torch.cuda.is_available()` returns False on an AMD card and an agent hunts for the cause.
- An LLM is deployed on AMD Instinct or EPYC through vLLM with the agent choosing settings.
- A model is quantized with AMD Quark and the result is verified.
- Image generation, text-to-speech and speech-to-text move to a local Lemonade server to cut token costs.
Not a fit when
- The project runs on another vendor's hardware: the skills target the AMD stack.
- You want general PyTorch advice with no tie to AMD GPUs.
- A skill is in Tech Preview while the project needs stable behaviour.
Example request
Use AMD Skills to deploy this LLM for inference on my AMD Instinct GPUs.Limitations
By the authors' own note the catalog is still being built in the open and changes often. Some skills are Tech Preview; check the status in the underlying product. The skills are vendored: copies from the ROCm, Lemonade and other team repositories live in `skills/`, with the source named in the README table. Skills such as `hyperloom-workload-optimizer` run optimization on real hardware, so compare the outcome with measurements.
How to disable. Delete the skill folders from the agent's skills directory (`~/.claude/skills/`, `.cursor/skills/` and similar). If installed through `skills`, `skills-lock.json` updates on the next CLI run.
FAQ
How do I install one skill instead of the whole catalog?
Add flags: `npx skills add amd/skills --skill local-ai-use --agent claude-code`. `npx skills add amd/skills --list` shows what is available.
Do I need to call a skill by hand?
Usually not: the agent picks a skill from its description. Explicit invocation is a fallback, for example asking to use AMD Skills in the prompt.
How do I install without npx?
Clone the repository and copy the skill folder from `skills/` into the agent's skills directory, such as `~/.claude/skills/` for Claude Code or `~/.cursor/skills/` for Cursor.
Where do the skills come from?
Each belongs to the team that owns its product (ROCm, Lemonade, Quark and others) and is vendored here. The registry lives in `.github/federation.json`.
Which agents run the AMD skills?
On Cursor, Claude Code, OpenAI Codex and Gemini CLI: the format is the standard Agent Skills.
Discussion
No questions or reviews yet.
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README in short
A skill here encodes an opinionated path: which flags, which container, which gfx target, in what order. Documentation stays neutral while a skill carries the choice.