Rapport d’audit du skill
magpie-kernel-evaluator Rapport d’audit.
Benchmarks LLM inference and drives GPU kernel optimization with Magpie. Use when the user wants to benchmark vLLM, SGLang, or Atom; capture torch traces; post-process inference traces with TraceLens into prefill/decode and roofline reports; identify top bottleneck kernels or map profiler names to source; analyze or compare HIP, CUDA, PyTorch, or Triton kernels; validate and rank optimized variants; run local, container, or Ray workloads; or mentions Magpie, TraceLens, gap analysis, TTFT, TPOT, kernel evaluation, or AMD GPU optimization.
Trust Score OpenAgentSkill
Trust Score OpenAgentSkill
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
Adoption GitHub
Info62
332 stars GitHub
Activité stars/forks
Avertissement57
332 stars et 30 forks; l’activité des issues n’est pas disponible dans les métadonnées actuelles
Maintenance récente
Validé88
1 mois depuis le dernier push
Clarté de licence
Validé86
MIT
Complétude README/SKILL.md
Validé86
Les métadonnées incluent suffisamment de contexte d’usage et de workflow
Risque dépendances/runtime
Avertissement44
command execution surface, credential or environment access
Disponibilité de l’installation
Validé92
npx skills add amd/skills --skill magpie-kernel-evaluator
Sécurité de la commande d’installation
Validé92
Chemin d’installation standard de package ou runtime
Surface de permissions
Échoué36
secrets or environment access, shell or command execution
Preuve du dépôt
Validé86
https://github.com/amd/skills/tree/main/skills/magpie-kernel-evaluator
État de revue
Validé88
Données de revue IA disponibles
Résultats prouvés par Agent
Info54
Pas encore de données de résultats Agent
Vérifications
Revue d’installation et d’adoption
Chemin d’installation
92
npx skills add amd/skills --skill magpie-kernel-evaluator
Dépôt
88
https://github.com/amd/skills/tree/main/skills/magpie-kernel-evaluator
Licence
86
MIT
Maintenance
88
1 mois depuis le dernier push
Revue IA
88
Approved with no listed issues
Complétude README/SKILL.md
86
Usable description available
Risque de dépendances
44
command execution surface, credential or environment access
Sécurité de la commande d’installation
92
Chemin d’installation standard de package ou runtime
Surface de permissions
36
secrets or environment access, shell or command execution
Activité stars/forks
57
332 stars et 30 forks; l’activité des issues n’est pas disponible dans les métadonnées actuelles
Adoption
68
332 stars GitHub
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Avertissements
- 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
- 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: 332 stars, 30 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
Méthode
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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