Informe de auditoría del skill
complete-ai-agent-stack-deployment-cloud-managed-from-scratch Informe de auditoría.
Sequences a complete, end-to-end AI agent stack deployment built on managed cloud services from scratch — a cloud landing zone, agent control-flow architecture, an LLM gateway routing across managed provider APIs (vendor-neutral: Anthropic/OpenAI/Azure OpenAI/Bedrock/ Vertex AI), a managed vector database for RAG, MCP servers for tool access, an evaluation-and-guardrails harness, and cost/latency monitoring. This is an integration/orchestration skill that sequences several existing tool-specific skills in the correct order and flags the handoff points between them — it does not restate their internals. Use when a user asks to "build a production AI agent stack using managed LLM APIs from scratch," "stand up an agent platform with a managed vector database and MCP tools," "give me the end-to-end sequence for a cloud-managed agent deployment," or "design the full pipeline from cloud account to a production agent with evals and cost monitoring."
Trust Score de OpenAgentSkill
Trust Score de OpenAgentSkill
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
Adopción en GitHub
Advertencia48
38 estrellas de GitHub
Actividad de stars/forks
Advertencia48
38 estrellas y 18 forks; la actividad de issues no está disponible en los metadatos actuales
Mantenimiento reciente
Aprobado88
3 meses desde el último push
Claridad de licencia
Aprobado86
Apache-2.0
Completitud de README/SKILL.md
Aprobado86
Los metadatos incluyen suficiente contexto de uso y flujo de trabajo
Riesgo de dependencias/runtime
Fallido38
command execution surface, credential or environment access
Disponibilidad de instalación
Aprobado92
npx skills add selvarajmurugesan90/ops-engineering-skills --skill complete-ai-agent-stack-deployment-cloud-managed-from-scratch
Seguridad del comando de instalación
Aprobado92
Ruta estándar de paquete o instalación en tiempo de ejecución
Superficie de permisos
Fallido18
secrets or environment access, shell or command execution
Evidencia del repositorio
Aprobado86
https://github.com/selvarajmurugesan90/ops-engineering-skills/tree/main/plugins/ai-agent/skills/complete-ai-agent-stack-deployment-cloud-managed-from-scratch
Estado de revisión
Advertencia46
Falta aprobación de revisión por IA
Resultados comprobados por Agent
Info54
Aún no hay datos de resultados del Agent
Comprobaciones
Revisión de instalación y adopción
Ruta de instalación
92
npx skills add selvarajmurugesan90/ops-engineering-skills --skill complete-ai-agent-stack-deployment-cloud-managed-from-scratch
Repositorio
88
https://github.com/selvarajmurugesan90/ops-engineering-skills/tree/main/plugins/ai-agent/skills/complete-ai-agent-stack-deployment-cloud-managed-from-scratch
Licencia
86
Apache-2.0
Mantenimiento
88
3 meses desde el último push
Revisión por IA
55
Review approval is missing
Completitud de README/SKILL.md
86
Usable description available
Riesgo de dependencias
38
command execution surface, credential or environment access
Seguridad del comando de instalación
92
Ruta estándar de paquete o instalación en tiempo de ejecución
Superficie de permisos
18
secrets or environment access, shell or command execution
Actividad de stars/forks
48
38 estrellas y 18 forks; la actividad de issues no está disponible en los metadatos actuales
Adopción
42
38 estrellas de GitHub
Advertencias
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Low GitHub adoption signal
- Falta aprobación de revisión por IA
- 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
- Review status: AI review approval is missing
Método
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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