hyperloom-workload-optimizer SKILL.md skillA
hyperloom-workload-optimizer from amd-agi/hyperloom is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add amd-agi/hyperloom/hyperloom-workload-optimizer@git:20260924.f2e2a9cPins git:20260924.f2e2a9c in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- amd-agi/hyperloom
- Path
examples/skills/hyperloom-workload-optimizer/SKILL.md- Versions recorded
- 2
- Latest version
- git:20260924.f2e2a9c, committed Sep 24, 2026
- First version recorded
- Sep 21, 2026
- Size
- 6,765 bytes
- Repository stars
- 262
- License
- a license file GitHub does not identify
Autonomously optimizes end-to-end LLM inference throughput on AMD Instinct GPUs and reports a validated gain, using the Hyperloom multi-agent optimizer. Given a model, framework, workload (TP/EP, concurrency, ISL/OSL, precision), an objective and a time budget, it explores per-workload which levers to pull (serving/config parameters and env, framework enablement and source patches, and hot GPU-kernel rewrites), benchmarks each candidate, and returns the optimization stack that produced the gain.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
<!-- Copyright (c) 2026 Advanced Micro Devices, Inc. All rights reserved. See LICENSE for license information. --> # Hyperloom Workload Optimizer You are the entry point for Hyperloom optimization on AMD Instinct GPUs. Your job is the bootstrap: confirm the workspace, install the Hyperloom wheel, run `/hyperloom-setup`, then hand the run to the skill that owns it. The wheel installs the skills that own everything after setup: `hyperloom-setup` for credentials and run mode, the demo skills for a workload preset, and `inference_optimizer` for the launcher gates and monitoring. They ship with the runtime, so they always match the installed version. ## Out of scope for this skill - Do not run `python -m hyperloom.inference_optimizer.cli optimize` yourself. - Do not implement a GPU preflight, launcher gate, or background launch here. The installed skills own those, including the Iron Rules and the resume path. - Do not ask for workload values (model, TP/EP, concurrency, ISL/OSL, precision, objective, budget) while installing or while setup is running. They belong to the run skill, after setup finishes. - Do not optimize by hand in chat. ## Prerequisites …
Read the whole file at its exact version.
How to install
mdr add amd-agi/hyperloom/hyperloom-workload-optimizer@sha256:baf471f98d4339b7The line at the top of this page pins the label git:20260924.f2e2a9c, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_vpjtx3gdhdggbkf7)
4 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 2 versions of this file, between Sep 21, 2026 and Sep 24, 2026, about one every 3 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260924.f2e2a9c latest | 2026-09-24 | f2e2a9c | 6,765 B | A | view · diff |
| git:20260921.1213b1b | 2026-09-21 | 1213b1b | 6,862 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (6765 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
amd-agi/hyperloom · 262 stars · license a license file GitHub does not identify · pushed 2026-11-06 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_vpjtx3gdhdggbkf7 GET https://markdownregistry.com/api/v1/resolve?ref=amd-agi/hyperloom/hyperloom-workload-optimizer GET https://markdownregistry.com/api/v1/blob/baf471f98d4339b735613586ca6c37e7b73ef42e58f35f1b2990f97b407c0f96
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.