Skill-Audit-Bericht
complete-ai-agent-stack-deployment-self-hosted-from-scratch Audit-Bericht.
Sequences a complete, end-to-end, fully self-hosted AI agent stack deployment from scratch — GPU procurement/sizing for open-weight model serving, self-hosted LLM serving (vLLM/TGI), agent control-flow architecture, a self-hosted vector database for RAG, self-hosted MCP servers for tool access, and an evaluation/guardrails harness — with no managed LLM API or managed vector database anywhere in the stack. An integration/orchestration skill that sequences existing tool-specific skills in the right order and flags handoff points, explicit about the added GPU-procurement and operational burden versus a cloud-managed agent stack. Use when a user asks to "build a self-hosted AI agent stack with open-weight models," "run our agent on our own GPUs with no managed LLM API," "stand up a self-hosted vector database and MCP servers for an agent platform," or "give me the end-to-end sequence for a fully self-hosted agent deployment from GPU procurement to production."
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
Warnung48
38 GitHub-Stars
Star-/Fork-Aktivität
Warnung48
38 Stars und 18 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbar
Aktuelle Wartung
Bestanden88
2 Monate seit dem letzten Push
Lizenzklarheit
Bestanden86
Apache-2.0
README/SKILL.md-Vollständigkeit
Bestanden86
Metadaten enthalten ausreichend Nutzungs- und Workflow-Kontext
Abhängigkeits-/Laufzeitrisiko
Fehlgeschlagen38
command execution surface, credential or environment access
Installationsverfügbarkeit
Bestanden92
npx skills add selvarajmurugesan90/ops-engineering-skills --skill complete-ai-agent-stack-deployment-self-hosted-from-scratch
Sicherheit des Installationsbefehls
Bestanden92
Standard-Paket- oder Laufzeit-Installationspfad
Berechtigungsumfang
Fehlgeschlagen24
secrets or environment access, shell or command execution
Repository-Nachweis
Bestanden86
https://github.com/selvarajmurugesan90/ops-engineering-skills/tree/main/plugins/ai-agent/skills/complete-ai-agent-stack-deployment-self-hosted-from-scratch
Prüfstatus
Warnung46
KI-Prüffreigabe fehlt
Agent-validierte Ergebnisse
Info54
Noch keine Agent-Ergebnisdaten
Prüfungen
Installations- und Adoptionsprüfung
Installationspfad
92
npx skills add selvarajmurugesan90/ops-engineering-skills --skill complete-ai-agent-stack-deployment-self-hosted-from-scratch
Repository
88
https://github.com/selvarajmurugesan90/ops-engineering-skills/tree/main/plugins/ai-agent/skills/complete-ai-agent-stack-deployment-self-hosted-from-scratch
Lizenz
86
Apache-2.0
Wartung
88
2 Monate seit dem letzten Push
KI-Prüfung
55
Review approval is missing
README/SKILL.md-Vollständigkeit
86
Usable description available
Abhängigkeitsrisiko
38
command execution surface, credential or environment access
Sicherheit des Installationsbefehls
92
Standard-Paket- oder Laufzeit-Installationspfad
Berechtigungsumfang
24
secrets or environment access, shell or command execution
Star-/Fork-Aktivität
48
38 Stars und 18 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbar
Akzeptanz
42
38 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
- Low GitHub adoption signal
- 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
- GitHub adoption: 38 GitHub stars
- Stars/forks activity: 38 stars, 18 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
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.
Nahe Optionen vergleichen
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