dojo.md
University for AI agents. 92 courses, 4400+ scenarios, any model via OpenRouter. Auto-training loops generate per-model SKILL.md documents. Works with Claude Code, OpenClaw, Cursor, Windsurf. No fine-tuning req...
Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when: (1) Setting up a team of 2+ agents with different specializations, (2) Defining task routing and lifecycle (inbox → spec → build → review → done), (3) Creating handoff protocols between agents, (4) Establishing review and quality gates, (5) Managing async communication and artifact sharing between agents.
Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.
SkillHub CLI
skillhub install arminnaimi/agent-team-orchestrationExaminez la source et la compatibilité, puis suivez les étapes d’installation.
Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.
Production playbook for running multi-agent teams with clear roles, structured task flow, and quality gates.
A builder and a reviewer. The simplest useful team.
Orchestrator (you) — Route tasks, track state, report results
Builder agent — Execute work, produce artifacts
1. Create task record (file, DB, or task board)
2. Spawn builder with:
- Task ID and description
- Output path for artifacts
- Handoff instructions (what to produce, where to put it)
3. On completion: review artifacts, mark done, report
Builder produces artifact → Reviewer checks it → Orchestrator ships or returns
That's the core loop. Everything below scales this pattern.
Every agent has one primary role. Overlap causes confusion.
| Role | Purpose | Model guidance |
|---|---|---|
| Orchestrator | Route work, track state, make priority calls | High-reasoning model (handles judgment) |
| Builder | Produce artifacts — code, docs, configs | Can use cost-effective models for mechanical work |
| Reviewer | Verify quality, push back on gaps | High-reasoning model (catches what builders miss) |
| Ops | Cron jobs, standups, health checks, dispatching | Cheapest model that's reliable |
→ Read references/team-setup.md when defining a new team or adding agents.
Every task moves through a defined lifecycle:
Inbox → Assigned → In Progress → Review → Done | Failed
Rules:
→ Read references/task-lifecycle.md when designing task flows or debugging stuck tasks.
When work passes b...
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# Agent Team Orchestration Production playbook for running multi-agent teams with clear roles, structured task flow, and quality gates. ## Quick Start: Minimal 2-Agent Team A builder and a reviewer. The simplest useful team. ### 1. Define Roles ``` Orchestrator (you) — Route tasks, track state, report results Builder agent — Execute work, produce artifacts ``` ### 2. Spawn a Task ``` 1. Create task record (file, DB, or task board) 2. Spawn builder with: - Task ID and description - Output path for artifacts - Handoff instructions (what to produce, where to put it) 3. On completion: review artifacts, mark done, report ``` ### 3. Add a Reviewer ``` Builder produces artifact → Reviewer checks it → Orchestrator ships or returns ``` That's the core loop. Everything below scales this pattern. ## Core Concepts ### Roles Every agent has one primary role. Overlap causes confusion. | Role | Purpose | Model guidance | |------|---------|---------------| | **Orchestrator** | Route work, track state, make priority calls | High-reasoning model (handles judgment) | | **Builder** | Produce artifacts — code, docs, configs | Can use cost-effective models for mechanical work | | **Reviewer** | Verify quality, push back on gaps | High-reasoning model (catches what builders miss) | | **Ops** | Cron jobs, standups, health checks, dispatching | Cheapest model that's reliable | → *Read [references/team-setup.md](references/team-setup.md) when defining a new team or adding agents.* ### Task States Every task moves through a defined lifecycle: ``` Inbox → Assigned → In Progress → Review → Done | Failed ``` **Rules:** - Orchestrator owns state transitions — don't rely on agents to update their own status - Every transition gets a comment (who, what, why) - Failed is a valid end state — capture why and move on → *Read [references/task-lifecycle.md](references/task-lifecycle.md) when designing task flows or debugging stuck tasks.* ### Handoffs When work passes b...
University for AI agents. 92 courses, 4400+ scenarios, any model via OpenRouter. Auto-training loops generate per-model SKILL.md documents. Works with Claude Code, OpenClaw, Cursor, Windsurf. No fine-tuning req...
macOS WPS Office workflow helper skill for safer document preparation, conversion, export, and compatibility guidance
A股分析技能
A2A4B2B Skill for OpenClaw