Skill-Audit-Bericht
hyperloom-workload-optimizer Audit-Bericht.
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.
OpenAgentSkill Trust Score
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub-Akzeptanz
Info62
395 GitHub-Stars
Star-/Fork-Aktivität
Warnung57
395 Stars und 39 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbar
Aktuelle Wartung
Bestanden100
5 Tage seit dem letzten Push
Lizenzklarheit
Bestanden86
MIT
README/SKILL.md-Vollständigkeit
Bestanden86
Metadaten enthalten ausreichend Nutzungs- und Workflow-Kontext
Abhängigkeits-/Laufzeitrisiko
Fehlgeschlagen36
command execution surface, credential or environment access
Installationsverfügbarkeit
Bestanden92
npx skills add amd/skills --skill hyperloom-workload-optimizer
Sicherheit des Installationsbefehls
Bestanden92
Standard-Paket- oder Laufzeit-Installationspfad
Berechtigungsumfang
Fehlgeschlagen22
secrets or environment access, shell or command execution
Repository-Nachweis
Bestanden86
https://github.com/amd/skills/tree/main/skills/hyperloom-workload-optimizer
Prüfstatus
Warnung46
KI-Prüffreigabe fehlt
Agent-validierte Ergebnisse
Info54
Noch keine Agent-Ergebnisdaten
Prüfungen
Installations- und Adoptionsprüfung
Installationspfad
92
npx skills add amd/skills --skill hyperloom-workload-optimizer
Repository
88
https://github.com/amd/skills/tree/main/skills/hyperloom-workload-optimizer
Lizenz
86
MIT
Wartung
100
5 Tage seit dem letzten Push
KI-Prüfung
55
Review approval is missing
README/SKILL.md-Vollständigkeit
86
Usable description available
Abhängigkeitsrisiko
36
command execution surface, credential or environment access
Sicherheit des Installationsbefehls
92
Standard-Paket- oder Laufzeit-Installationspfad
Berechtigungsumfang
22
secrets or environment access, shell or command execution
Star-/Fork-Aktivität
57
395 Stars und 39 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbar
Akzeptanz
68
395 GitHub-Stars
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Warnungen
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Financial research output is not financial advice; require human review before any live investment decision
- KI-Prüffreigabe fehlt
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- Stars/forks activity: 395 stars, 39 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- Review status: AI review approval is missing
Methode
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
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