Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
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sayasaya8039/ZWG_Terminal22026年6月8日 更新
免费在 GitHub 公开
continuous-agent-loop
Patterns for continuous autonomous agent loops with quality gates, evals, and recovery controls.
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查看安装方法包含的文件（1）
- SKILL.md1.1 KB
SKILL.md（原文）
安装前可以查看交给 AI 代理的指令内容。
Continuous Agent Loop
This is the v1.8+ canonical loop skill name. It supersedes autonomous-loops while keeping compatibility for one release.
Loop Selection Flow
Start
|
+-- Need strict CI/PR control? -- yes --> continuous-pr
|
+-- Need RFC decomposition? -- yes --> rfc-dag
|
+-- Need exploratory parallel generation? -- yes --> infinite
|
+-- default --> sequential
Combined Pattern
Recommended production stack:
- RFC decomposition (
ralphinho-rfc-pipeline) - quality gates (
plankton-code-quality+/quality-gate) - eval loop (
eval-harness) - session persistence (
nanoclaw-repl)
Failure Modes
- loop churn without measurable progress
- repeated retries with same root cause
- merge queue stalls
- cost drift from unbounded escalation
Recovery
- freeze loop
- run
/harness-audit - reduce scope to failing unit
- replay with explicit acceptance criteria
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