LangGraph-based agentic loop engine for IDE/CLI environments — enforces think→execute→critique→refine on every coding action
Project description
name: global-loop-engine description: 全局 Loop Engineering 引擎,强制 Agent 执行时使用基于 LangGraph 的反思和验证循环机制。
全局 Loop Engineering (Global Loop Engine)
此 Skill 强制 Agent 在执行任何核心开发或复杂任务时,必须通过内部循环和严格校验后才可提交结果,遵循“热冷分离”原则并执行硬核校验。
核心节点机制
- 复杂性评分 (ComplexityScorerNode):评估当前任务的代码逻辑复杂度和受影响文件范围。
- 成本估算 (CostEstimatorNode):根据复杂度和循环执行预估执行成本(Token / 时间)。
- 严重验证器 (CriticNode):
- 硬核校验:基于子进程 (
subprocess) 调用真实测试框架(如pytest)、静态分析(如pylint/grep)。 - 热冷分离:严格保存并分离运行时结果(如
Exit Code)与代码状态快照(如Git Diff),以供客观评估判断是否能够通过验收。
- 硬核校验:基于子进程 (
执行准则
当此 Skill 生效时,Agent 不得直接输出"我完成了",必须首先运行配套的引擎:
# 方式一(推荐):通过 CLI 入口
loop-engine --task "<当前任务描述>"
# 方式二:直接调用脚本
python scripts/loop_engine.py --task "<当前任务描述>"
引擎若给出错误(非 0 exit code)或处于尚未满足验收退出条件时,必须根据反馈继续修复代码,直到验证通过(退出节点)才可进行汇报。
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