Skill-Audit-Bericht
vllm-model-tutorial Audit-Bericht.
Generate comprehensive Chinese technical tutorial documents for specific vLLM models (e.g., Qwen3-VL, DeepSeek-V3, Llama 4, InternVL3, etc.). Produces deep-dive model walkthrough documents with Mermaid architecture diagrams, comparison tables, input preprocessing flows, forward pass analysis, ViT computation (for VLMs), vLLM code implementation analysis, and technical principle explanations (MoE, MLA, Gated Attention, ViT, DiT, etc.). Output is saved as Markdown to the skill's outputs/ directory. TRIGGER when: user asks to learn about a specific vLLM model (e.g., "我想了解 vllm 中的 Qwen3-VL", "帮我生成 Qwen3-VL 的模型教程", "generate a model tutorial for InternVL3 in vllm", "vllm 中的 DeepSeek-V3 是怎么实现的", "写一个 Llama 4 的vllm教程"). DO NOT TRIGGER when: user asks about non-vLLM models, general LLM questions without requesting a tutorial, or asks about vLLM features/modules rather than specific models.
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
Fehlgeschlagen30
20 GitHub-Stars
Star-/Fork-Aktivität
Fehlgeschlagen32
20 Stars und 3 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbar
Aktuelle Wartung
Bestanden100
5 Tage seit dem letzten Push
Lizenzklarheit
Bestanden86
Apache-2.0
README/SKILL.md-Vollständigkeit
Bestanden86
Metadaten enthalten ausreichend Nutzungs- und Workflow-Kontext
Abhängigkeits-/Laufzeitrisiko
Warnung54
command execution surface, credential or environment access
Installationsverfügbarkeit
Bestanden92
npx skills add shen-shanshan/vllm-dev-skills --skill vllm-model-tutorial
Sicherheit des Installationsbefehls
Bestanden92
Standard-Paket- oder Laufzeit-Installationspfad
Berechtigungsumfang
Fehlgeschlagen36
secrets or environment access, shell or command execution
Repository-Nachweis
Bestanden86
https://github.com/shen-shanshan/vllm-dev-skills/tree/master/skills/vllm-model-tutorial
Prüfstatus
Warnung46
KI-Prüffreigabe fehlt
Agent-validierte Ergebnisse
Info54
Noch keine Agent-Ergebnisdaten
Prüfungen
Installations- und Adoptionsprüfung
Installationspfad
92
npx skills add shen-shanshan/vllm-dev-skills --skill vllm-model-tutorial
Repository
88
https://github.com/shen-shanshan/vllm-dev-skills/tree/master/skills/vllm-model-tutorial
Lizenz
86
Apache-2.0
Wartung
100
5 Tage seit dem letzten Push
KI-Prüfung
55
Review approval is missing
README/SKILL.md-Vollständigkeit
86
Usable description available
Abhängigkeitsrisiko
54
command execution surface, credential or environment access
Sicherheit des Installationsbefehls
92
Standard-Paket- oder Laufzeit-Installationspfad
Berechtigungsumfang
36
secrets or environment access, shell or command execution
Star-/Fork-Aktivität
32
20 Stars und 3 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbar
Akzeptanz
42
20 GitHub-Stars
Warnungen
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Low GitHub adoption signal
- KI-Prüffreigabe fehlt
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 20 GitHub stars
- Stars/forks activity: 20 stars, 3 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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