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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.

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查看安装方法

包含的文件(2)

  • SKILL.md1.9 KB
  • agents/openai.yaml406 B

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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.

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