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Operate long-lived agent workloads with observability, security boundaries, and lifecycle management.
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Based on SOC occupation classification
Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing.
Engineering operating model for teams where AI agents generate a large share of implementation output.
Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code.
Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns.
| name | enterprise-agent-ops |
| description | Operate long-lived agent workloads with observability, security boundaries, and lifecycle management. |
| source_path | skills/enterprise-agent-ops/SKILL.md |
| origin | ECC |
Use this skill for cloud-hosted or continuously running agent systems that need operational controls beyond single CLI sessions.
When failure spikes:
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