Skip to main content

agent-orchestration

AI DevKit · Supervise multi-agent workflows over repeated passes: poll progress, unblock waiting agents, coordinate dependencies, relay outputs, resolve conflicts, and verify completion. Use only for ongoing multi-agent coordination, not one-off list/detail/send/start/kill actions.

来源信息

仓库
codeaholicguy/ai-devkit
最近来源活动
2026年10月23日 13:29
检测到的 SKILL.md 语言
英语
星标
1,652
Forks
259

安装方式

默认使用会先检查来源的 Prompt;你也可以切换为直接命令,或下载本地副本。

检查来源文件

决定是否安装前,请先阅读 SKILL.md,以及 SkillsMP 当前展示的配套文件。

文件资源管理器
2 个文件

正在显示 SKILL.md

SKILL.md
来源说明 · 只读预览
name
agent-orchestration
description
AI DevKit · Supervise multi-agent workflows over repeated passes: poll progress, unblock waiting agents, coordinate dependencies, relay outputs, resolve conflicts, and verify completion. Use only for ongoing multi-agent coordination, not one-off list/detail/send/start/kill actions.
# Agent Orchestration Use only for multi-agent supervision: coordinating dependencies, polling progress, unblocking waiting agents, relaying outputs, resolving conflicts, and verifying completion across agents. For one-off list/detail/send/start/kill work, use `agent-management` or `agent-communication`. Use `agent-management` for safe agent selection and lifecycle actions. Use `agent-communication` for list/detail/send mechanics. Use `verify` before accepting any agent's completion claim. ## Rules - Own the loop until assigned work is complete, blocked, or stopped. - Run `agent list --json` before each pass; never assume names/statuses. - Inspect waiting, idle, unknown, missing, or stale agents before acting. - Send self-contained instructions and avoid duplicate follow-ups. - Sequence agents that touch the same files; relay only relevant upstream output. - Escalate only for repeated failures, unresolved conflicts, product/business decisions, or destructive/shared/production/security-sensitive actions. ## Loop If the goal or agent ownership is unclear, run one scan/detail pass. Ask the user once only if context is still insufficient. 1. Scan agents. 2. Assess agents needing attention with `detail --tail 10`. 3. Act: approve, clarify, correct, delegate, relay, verify, or escalate. 4. Report one brief status line. 5. Sleep 10-60s and repeat. ## Completion Finish when all assigned work is verified, blocked with a clear reason, or stopped by the user. Summarize per-agent outcomes, verification, unresolved issues, and next step.
在 GitHub 查看