do-agent

SkillProductivity

Lets your agent break a big task into a multi-stage plan and run up to 10 parallel sub-agents to complete it.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the do-agent skill

About this capability

This skill should be used when the user asks to "/do-agent", asks for "Execute complex tasks using multi-agent architecture with context protection", or needs the workflow previously provided by the /do-agent slash command.

What this skill tells your AI

The instructions your AI receives, as published by brycewang-stanford/auto-empirical-research-skills in skills/67-econfin-workflow-toolkit/do-agent/SKILL.md and read by ahel’s review.

Explore and ultrathink to design a systematic multi-agent, multi-stage (up to 10 subagents in parallel in each stage) execution plan to accomplish: $ARGUMENTS

执行模式:explore → ultrathink → plan → track → execute → review → revise → deliver final output

Note:

  • Get the current Date and Time (Beijing time)
  • 创建临时工作目录 agent_tasks/{short task description}_yyyyddmmhh/ 作为临时工作空间(if a folder with this name already exists, make a new one to avoid overwriting existing materals)
  • When assigning tasks to subagents, specify their input and output files explicitly
  • 每个子代理必须自己将处理结果立即保存到本地文件,不要返回给主代理!子代理自己马上保存,不要返回给主代理!
  • 严禁将子代理完整输出返回主代理;只返回状态摘要
  • 第一个本地输出文件:multi-agent execution plan 文档 agent_tasks/{short task description}_yyyyddmmhh/plan.md
  • The main/mother agent must allow all Read + Write + Bash tools for all sub-agents
  • Apply context engineering — main agent context is scarce
  • The execution plan must include (at minimum) these four phases, each with multiple agents (in parallel when possible):
    1. 规划阶段:信息收集与方案规划
    2. 实施阶段:执行与整合任务结果
    3. 对任务结果进行审阅与反馈
    4. 根据审阅反馈,对任务结果进行全面修订
  • Do not ask for plan approval, just set up the tasks tracking and do it once the planning phase finished
  • Complete automation of the entire process, from planning to execution to review and revision, without any human intervention

Signals

GitHub stars
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Forks
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Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
do-agent
Source
github.com/brycewang-stanford/auto-empirical-research-skills