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Patterns for continuous autonomous agent loops with quality gates, evals, and recovery controls.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
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 | continuous-agent-loop |
| description | Patterns for continuous autonomous agent loops with quality gates, evals, and recovery controls. |
| source_path | skills/continuous-agent-loop/SKILL.md |
| origin | ECC |
This is the v1.8+ canonical loop skill name. It supersedes autonomous-loops while keeping compatibility for one release.
Start
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+-- Need strict CI/PR control? -- yes --> continuous-pr
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+-- Need RFC decomposition? -- yes --> rfc-dag
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+-- Need exploratory parallel generation? -- yes --> infinite
|
+-- default --> sequential
Recommended production stack:
ralphinho-rfc-pipeline)plankton-code-quality + /quality-gate)eval-harness)nanoclaw-repl)/harness-audit