agent-orchestration
Agent Orchestration is a Claude Code skill that manages multi-agent workflows by continuously monitoring agent statuses, tracking progress, sending targeted instructions, and coordinating work across multiple agents without requiring user intervention between steps. Use this skill when managing complex projects with multiple specialized agents, coordinating parallel or sequential agent tasks, or maintaining oversight of agent progress and automatically resolving issues or escalating blockers to the user.
git clone --depth 1 https://github.com/codeaholicguy/ai-devkit /tmp/agent-orchestration && cp -r /tmp/agent-orchestration/skills/agent-orchestration ~/.claude/skills/agent-orchestrationSKILL.md
# 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.
AI DevKit · Compare implementation with design and requirements docs to ensure alignment.
AI DevKit · Pre-push code review against design docs.
AI DevKit · Execute a feature plan task by task.
AI DevKit · Scaffold feature documentation from requirements through planning.
AI DevKit · Store reusable guidance in the knowledge memory service.
AI DevKit · Review feature design for completeness.
AI DevKit · Review feature requirements for completeness.
AI DevKit · Update planning docs to reflect implementation progress.