Rapport d’audit du skill
complete-ai-agent-stack-deployment-self-hosted-from-scratch Rapport d’audit.
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."
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
Avertissement48
38 stars GitHub
Activité stars/forks
Avertissement48
38 stars et 18 forks; l’activité des issues n’est pas disponible dans les métadonnées actuelles
Maintenance récente
Validé88
3 mois depuis le dernier push
Clarté de licence
Validé86
Apache-2.0
Complétude README/SKILL.md
Validé86
Les métadonnées incluent suffisamment de contexte d’usage et de workflow
Risque dépendances/runtime
Échoué38
command execution surface, credential or environment access
Disponibilité de l’installation
Validé92
npx skills add selvarajmurugesan90/ops-engineering-skills --skill complete-ai-agent-stack-deployment-self-hosted-from-scratch
Sécurité de la commande d’installation
Validé92
Chemin d’installation standard de package ou runtime
Surface de permissions
Échoué24
secrets or environment access, shell or command execution
Preuve du dépôt
Validé86
https://github.com/selvarajmurugesan90/ops-engineering-skills/tree/main/plugins/ai-agent/skills/complete-ai-agent-stack-deployment-self-hosted-from-scratch
État de revue
Avertissement46
L’approbation de revue IA est absente
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 selvarajmurugesan90/ops-engineering-skills --skill complete-ai-agent-stack-deployment-self-hosted-from-scratch
Dépôt
88
https://github.com/selvarajmurugesan90/ops-engineering-skills/tree/main/plugins/ai-agent/skills/complete-ai-agent-stack-deployment-self-hosted-from-scratch
Licence
86
Apache-2.0
Maintenance
88
3 mois depuis le dernier push
Revue IA
55
Review approval is missing
Complétude README/SKILL.md
86
Usable description available
Risque de dépendances
38
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
24
secrets or environment access, shell or command execution
Activité stars/forks
48
38 stars et 18 forks; l’activité des issues n’est pas disponible dans les métadonnées actuelles
Adoption
42
38 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
- Low GitHub adoption signal
- L’approbation de revue IA est absente
- 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
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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