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Do In Steps

技能 已验证 活跃

Execute complex tasks through sequential sub-agent orchestration with intelligent model selection, meta-judge → LLM-as-a-judge verification

目的

To execute complex, multi-step tasks reliably by intelligently decomposing them, selecting optimal agents, and ensuring quality through rigorous verification at each stage.

功能

  • Sequential sub-agent orchestration
  • Automatic task decomposition
  • Intelligent model and agent selection
  • Parallel execution of meta-judge and implementer agents
  • LLM-as-a-judge verification with scoring and iteration
  • Context passing between steps

使用场景

  • Refactoring large codebases across multiple files
  • Implementing complex features with distinct stages
  • Automating software development workflows with quality gates
  • Handling tasks requiring specialized agents for different sub-problems

非目标

  • Directly performing the task implementation itself
  • Skipping task decomposition or verification steps
  • Overriding the orchestrated sub-agent workflow
  • Performing tasks that do not require sequential execution or sub-agent involvement

工作流

  1. Analyze and decompose the task into sequential subtasks
  2. Select optimal models and agents for each subtask
  3. For each step, dispatch meta-judge and implementation agent in parallel
  4. Wait for both to complete, then dispatch judge with meta-judge's specification
  5. Iterate if judge fails the step (max 3 retries)
  6. Collect outputs and pass context forward
  7. Report final results

实践

  • Orchestration
  • Agent Workflow
  • Verification
  • Task Decomposition

安装

请先添加 Marketplace

/plugin marketplace add NeoLabHQ/context-engineering-kit
/plugin install sadd@context-engineering-kit

质量评分

已验证
97 /100
1 day ago 分析

信任信号

最近提交9 days ago
星标993
许可证GPL-3.0-or-later
状态
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