# Send Agent Orchestrator to your agent
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
## Fast path
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
## Suggested prompts
### New install

```text
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
```
### Upgrade existing

```text
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
```
## Machine-readable fields
```json
{
  "schemaVersion": "1.0",
  "item": {
    "slug": "agent-orchestrator",
    "name": "Agent Orchestrator",
    "source": "tencent",
    "type": "skill",
    "category": "AI 智能",
    "sourceUrl": "https://clawhub.ai/aatmaan1/agent-orchestrator",
    "canonicalUrl": "https://clawhub.ai/aatmaan1/agent-orchestrator",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadUrl": "/downloads/agent-orchestrator",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=agent-orchestrator",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "packageFormat": "ZIP package",
    "primaryDoc": "SKILL.md",
    "includedAssets": [
      "SKILL.md",
      "references/communication-protocol.md",
      "references/sub-agent-templates.md"
    ],
    "downloadMode": "redirect",
    "sourceHealth": {
      "source": "tencent",
      "slug": "agent-orchestrator",
      "status": "healthy",
      "reason": "direct_download_ok",
      "recommendedAction": "download",
      "checkedAt": "2026-04-29T07:10:39.268Z",
      "expiresAt": "2026-05-06T07:10:39.268Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=agent-orchestrator",
      "contentType": "application/zip",
      "probeMethod": "head",
      "details": {
        "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=agent-orchestrator",
        "contentDisposition": "attachment; filename=\"agent-orchestrator-0.1.0.zip\"",
        "redirectLocation": null,
        "bodySnippet": null,
        "slug": "agent-orchestrator"
      },
      "scope": "item",
      "summary": "Item download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this item.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/agent-orchestrator"
    },
    "validation": {
      "installChecklist": [
        "Use the Yavira download entry.",
        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
      ]
    }
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/agent-orchestrator",
    "downloadUrl": "https://openagent3.xyz/downloads/agent-orchestrator",
    "agentUrl": "https://openagent3.xyz/skills/agent-orchestrator/agent",
    "manifestUrl": "https://openagent3.xyz/skills/agent-orchestrator/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/agent-orchestrator/agent.md"
  }
}
```
## Documentation

### Agent Orchestrator

Orchestrate complex tasks by decomposing them into subtasks, spawning autonomous sub-agents, and consolidating their work.

### Phase 1: Task Decomposition

Analyze the macro task and break it into independent, parallelizable subtasks:

1. Identify the end goal and success criteria
2. List all major components/deliverables required
3. Determine dependencies between components
4. Group independent work into parallel subtasks
5. Create a dependency graph for sequential work

Decomposition Principles:

Each subtask should be completable in isolation
Minimize inter-agent dependencies
Prefer broader, autonomous tasks over narrow, interdependent ones
Include clear success criteria for each subtask

### Phase 2: Agent Generation

For each subtask, create a sub-agent workspace:

python3 scripts/create_agent.py <agent-name> --workspace <path>

This creates:

<workspace>/<agent-name>/
âââ SKILL.md          # Generated skill file for the agent
âââ inbox/            # Receives input files and instructions
âââ outbox/           # Delivers completed work
âââ workspace/        # Agent's working area
âââ status.json       # Agent state tracking

Generate SKILL.md dynamically with:

Agent's specific role and objective
Tools and capabilities needed
Input/output specifications
Success criteria
Communication protocol

See references/sub-agent-templates.md for pre-built templates.

### Phase 3: Agent Dispatch

Initialize each agent by:

Writing task instructions to inbox/instructions.md
Copying required input files to inbox/
Setting status.json to {"state": "pending", "started": null}
Spawning the agent using the Task tool:

# Spawn agent with its generated skill
Task(
    description=f"{agent_name}: {brief_description}",
    prompt=f"""
    Read the skill at {agent_path}/SKILL.md and follow its instructions.
    Your workspace is {agent_path}/workspace/
    Read your task from {agent_path}/inbox/instructions.md
    Write all outputs to {agent_path}/outbox/
    Update {agent_path}/status.json when complete.
    """,
    subagent_type="general-purpose"
)

### Phase 4: Monitoring (Checkpoint-based)

For fully autonomous agents, minimal monitoring is needed:

# Check agent completion
def check_agent_status(agent_path):
    status = read_json(f"{agent_path}/status.json")
    return status.get("state") == "completed"

Periodically check status.json for each agent. Agents update this file upon completion.

### Phase 5: Consolidation

Once all agents complete:

Collect outputs from each agent's outbox/
Validate deliverables against success criteria
Merge/integrate outputs as needed
Resolve conflicts if multiple agents touched shared concerns
Generate summary of all work completed

# Consolidation pattern
for agent in agents:
    outputs = glob(f"{agent.path}/outbox/*")
    validate_outputs(outputs, agent.success_criteria)
    consolidated_results.extend(outputs)

### Phase 6: Dissolution & Summary

After consolidation:

Archive agent workspaces (optional)
Clean up temporary files
Generate final summary:

What was accomplished per agent
Any issues encountered
Final deliverables location
Time/resource metrics

python3 scripts/dissolve_agents.py --workspace <path> --archive

### File-Based Communication Protocol

See references/communication-protocol.md for detailed specs.

Quick Reference:

inbox/ - Read-only for agent, written by orchestrator
outbox/ - Write-only for agent, read by orchestrator
status.json - Agent updates state: pending â running â completed | failed

### Example: Research Report Task

Macro Task: "Create a comprehensive market analysis report"

Decomposition:
âââ Agent: data-collector
â   âââ Gather market data, competitor info, trends
âââ Agent: analyst
â   âââ Analyze collected data, identify patterns
âââ Agent: writer
â   âââ Draft report sections from analysis
âââ Agent: reviewer
    âââ Review, edit, and finalize report

Dependency: data-collector â analyst â writer â reviewer

### Sub-Agent Templates

Pre-built templates for common agent types in references/sub-agent-templates.md:

Research Agent - Web search, data gathering
Code Agent - Implementation, testing
Analysis Agent - Data processing, pattern finding
Writer Agent - Content creation, documentation
Review Agent - Quality assurance, editing
Integration Agent - Merging outputs, conflict resolution

### Best Practices

Start small - Begin with 2-3 agents, scale as patterns emerge
Clear boundaries - Each agent owns specific deliverables
Explicit handoffs - Use structured files for agent communication
Fail gracefully - Agents report failures; orchestrator handles recovery
Log everything - Status files track progress for debugging
## Trust
- Source: tencent
- Verification: Indexed source record
- Publisher: aatmaan1
- Version: 0.1.0
## Source health
- Status: healthy
- Item download looks usable.
- Yavira can redirect you to the upstream package for this item.
- Health scope: item
- Reason: direct_download_ok
- Checked at: 2026-04-29T07:10:39.268Z
- Expires at: 2026-05-06T07:10:39.268Z
- Recommended action: Download for OpenClaw
## Links
- [Detail page](https://openagent3.xyz/skills/agent-orchestrator)
- [Send to Agent page](https://openagent3.xyz/skills/agent-orchestrator/agent)
- [JSON manifest](https://openagent3.xyz/skills/agent-orchestrator/agent.json)
- [Markdown brief](https://openagent3.xyz/skills/agent-orchestrator/agent.md)
- [Download page](https://openagent3.xyz/downloads/agent-orchestrator)