amd-skills — 8 skills

Pinned source listing — machine-checked

What declarations and files are present in this pinned source?

Pinned source declarations and file hashes were listed.

Review

Machine-checked · 2026-10-18

Run UTC: 2026-10-17T18:13:44Z
Reviewed: 2026-10-18
Published: 2026-10-18
Updated: 2026-10-18

Observations · Limitations · Evidence

What we ran

Git blob acquisition followed by static source inspection.

What we saw

Listed 8 skill declarations. Ran 162 git commands; each one's exit status and output hash is in commands.json. Scope: acquisition and static inspection.

Limits

Scope: acquisition and static inspection. Command results: commands.json.

developer-tools · skills · Upstream source · Upstream documentation

Pinned source inspection only; no runtime platform was exercised. UTC 2026-10-17T18:13:44Z, tree 9552af3801aefe2fac18c134c8b31523d02027b7e1135fcb4bc78f29c61a2be3.

No browser or computer-use tools. Pin this exact version; the stamp does not follow updates.

Full record

name: amd-skills — 8 skills
slug: source-skills-3f7f8a32118b785b3723a704
type: skills
category: developer-tools
example: false
evidence state: pinned_source_listing
stamp: Pinned source listing — machine-checked
summary: Pinned source declarations and file hashes were listed.
outcome: Listed 8 skill declarations. Ran 162 git commands; each one's exit status and output hash is in commands.json. Scope: acquisition and static inspection.
rule results: ["The retained source tree matches its acquisition manifest.","Declared skill names (listing.json): hyperloom-workload-optimizer; lemonade-router-builder; local-ai-app-integration; local-ai-use; magpie-kernel-evaluator; serving-llms-on-epyc; serving-llms-on-instinct; tracelens-analysis-orchestrator"]
task: What declarations and files are present in this pinned source?
setup: Git blob acquisition followed by static source inspection.
limitations: Scope: acquisition and static inspection. Command results: commands.json.
source url: https://github.com/amd/skills.git
documentation url: https://github.com/amd/skills.git
commit: 6916fb371d1cba40757b223cf16b4cd4912b202f
tree sha256: 9552af3801aefe2fac18c134c8b31523d02027b7e1135fcb4bc78f29c61a2be3
file sha256: 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lockfiles: ["LOCK.json"]
utc date: 2026-10-17T18:13:44Z
source date: 2026-10-16
discovered date: 2026-10-16
retested date: 2026-10-17
reviewed date: 2026-10-18
published date: 2026-10-18
modified date: 2026-10-18
reviewer: Machine-checked
harness version: toolwitness harness at commit 91d582437af1f2e02c76d72bbea545f817acfaa1
claude code version: Not applicable: static source inspection (commands.json).
model id: Not applicable: static source inspection (commands.json).
scanner version: Not applicable: static source inspection.
rulepack version: Not applicable: static source inspection.
agents: []
commands: ["Ran 162 git commands; each one's exit status and output hash is in commands.json. Scope: acquisition and static inspection."]
prompt list: ["Not applicable: static source inspection (commands.json)."]
history: ["2026-10-17T18:13:44Z: pinned source inspection"]
application: {"applicationCategory":"DeveloperApplication","name":"amd-skills — 8 skills","operatingSystem":"Not exercised","softwareVersion":"6916fb371d1cba40757b223cf16b4cd4912b202f"}
review input: {"claims":[{"field":"summary","id":"acquired","sources":["LOCK.json","listing.json","commands.json"],"text":"Pinned source declarations and file hashes were listed."},{"field":"outcome","id":"listed","sources":["LOCK.json","listing.json","commands.json"],"text":"Listed 8 skill declarations. Ran 162 git commands; each one's exit status and output hash is in commands.json. Scope: acquisition and static inspection."},{"field":"rule_results.0","id":"tree","sources":["LOCK.json","listing.json","commands.json"],"text":"The retained source tree matches its acquisition manifest."},{"field":"rule_results.1","id":"declared","sources":["LOCK.json","listing.json","commands.json"],"text":"Declared skill names (listing.json): hyperloom-workload-optimizer; lemonade-router-builder; local-ai-app-integration; local-ai-use; magpie-kernel-evaluator; serving-llms-on-epyc; serving-llms-on-instinct; tracelens-analysis-orchestrator"}],"evidence_sha256":{"LOCK.json":"3977da560d94c4968974a096dfed765863cdba72549a7e1d3b31e6291f2b718f","commands.json":"e847ff9c6e79a7b6286ab86a001d565f21acacb77422217fcd5c2a0e2746cb82","complete.json":"91b504b43905fdc009504d516c45eea831f39a1995b9e7d69987c9756c936d6f","identity.json":"08798960d7a42e4bca3cb97039139d5a0e023707f24dbea7926693d69cdd4467","listing.json":"ee51f905ccd21d79c1928319934d500c99154e331d00a42733cb8ace2bc1a802","selection.json":"0ee6cf5e2f4ac80ffc4bfc9e72e290a9fb8ed9071f6f87aa9ccbfb1f0280b786"},"identity_artifact":"identity.json"}
review: {"codex":"7595966a1a7dfa8839f4603d1335c290b78c7edd109a7c752ebac2b7550e1bbc","date":"2026-10-18","gates":"727fd595912246e98ed642fe192d0858d87b18fabfddd5af4ad3d7b5634b0f27","grok":"b9a081390fa68046331d4b1270d05a610f51294d1636cc8c444e01957f816a8f","kind":"machine-checked","reviewed_sha256":"aca840dd4a9291020b06a600a3f7c6930c58674bc3a82c9c355391179d7fbc76","summary":"Deterministic gates passed; Codex confirmed all outcome claims; Grok reported no standing refutation."}

Downloadable evidence

transcript

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Ran 162 git commands; each one's exit status and output hash is in commands.json. Scope: acquisition and static inspection.

sinkhole log

Download complete sinkhole log

Not applicable: static source inspection (commands.json).

canary log

Download complete canary log

Not applicable: static source inspection (commands.json).

scanner output

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Not applicable: static source inspection (commands.json).

normalized text

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{
  "listing": {
    "skills": [
      {
        "path": "skills/hyperloom-workload-optimizer/SKILL.md",
        "name": "hyperloom-workload-optimizer",
        "description": "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. Use when the user wants to make a model serve faster, raise tokens/sec or throughput, optimize or tune vLLM or SGLang on MI300X/MI325X/MI355X, run Hyperloom, run the kernel-agent, quantize-then-optimize with Quark, set up Hyperloom from scratch, or resume a Hyperloom session. Do not use to stand up a server for plain serving, diagnose a broken ROCm install, or run a one-off kernel/benchmark or trace analysis without the optimization loop.",
        "files": {
          "skills/hyperloom-workload-optimizer/SKILL.md": "e3005372990310e527182cd56c651281c017a64cb57d2d5979001212bdf56bd6",
          "skills/hyperloom-workload-optimizer/evals/evals.json": "7f254fb5fe96c17f8fe46f20e379ed7887af2e320ae2a43b7223b1f2d0c68bbd",
          "skills/hyperloom-workload-optimizer/evals/machine.yml": "3a53df46087df6eef3a243aab68875ab2f67400abf1838b61d5a0420e951f29c",
          "skills/hyperloom-workload-optimizer/reference.md": "50f2a2cd3277379397828096779b79394ba6825eaf84f5dac63730c984f837fa",
          "skills/hyperloom-workload-optimizer/scripts/_env.sh": "8a9cd34a91d4b920387a87d9ba8af9f2735b408585257b3f89e893dc54bdc1ee",
          "skills/hyperloom-workload-optimizer/scripts/launch.sh": "25b44c1705334e64ccba7699db7b3169e59bcf3cd5463c29606a544d221ad730",
          "skills/hyperloom-workload-optimizer/scripts/launch_hea

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