amoa-messaging-templates
Use when sending inter-agent messages. Trigger with task assignment, status report, or escalation needs. Loaded by ai-maestro-orchestrator-agent-main-agent
Best use case
amoa-messaging-templates is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Use when sending inter-agent messages. Trigger with task assignment, status report, or escalation needs. Loaded by ai-maestro-orchestrator-agent-main-agent
Teams using amoa-messaging-templates should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/amoa-messaging-templates/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How amoa-messaging-templates Compares
| Feature / Agent | amoa-messaging-templates | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Use when sending inter-agent messages. Trigger with task assignment, status report, or escalation needs. Loaded by ai-maestro-orchestrator-agent-main-agent
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# AMOA Shared Communication Templates
## Overview
Reusable JSON message templates for agent coordination, task assignment, status reporting, and escalation.
## Prerequisites
1. AI Maestro messaging system (AMP) running
2. Understanding of ai-maestro agent roles (AMOA, AMCOS, AMIA, AMAMA)
3. Access to AI Maestro API; read **amoa-label-taxonomy** for GitHub label usage
## Instructions
1. Identify the communication scenario (task assignment, status report, approval, escalation)
2. Select the appropriate template from section 2 reference files
3. Fill in template fields with task-specific values
4. Send via `agent-messaging` skill and wait for response
5. Log the exchange in the delegation log
Copy this checklist and track your progress:
- [ ] Identify communication scenario (task assignment, status report, approval, escalation)
- [ ] Select the appropriate template from section 2
- [ ] Fill in template fields and send via `agent-messaging` skill
- [ ] Wait for response and log the exchange in the delegation log
## 1. AI Maestro Message Format
Standard JSON message structure with from, to, subject, priority, and content fields. See: [references/message-format.md](references/message-format.md)
<!-- TOC: Standard Message Structure | Sending Messages | Checking Inbox -->
## 2. Message Templates by Scenario
JSON templates: [references/message-templates.md](references/message-templates.md)
<!-- TOC: 1 Task Assignment (AMOA to Remote Agent) | 2 Task Completion Report (Agent to AMOA) | 3 Status Request (AMOA to Agent) | 4 Status Response (Agent to AMOA) | 5 Approval Request (AMCOS to AMAMA) | 6 Approval Response (AMAMA to AMCOS) | 7 Escalation (Any Agent to AMCOS/AMAMA) | 8 Acknowledgment (Any Agent) | 9 Design Handoff (AMAA to AMOA) | 10 Integration Request (AMOA to AMIA) | 11 Integration Result (AMIA to AMOA) | Decision Trees for Core Message Templates -->
Curl templates: [references/ai-maestro-message-templates.md](references/ai-maestro-message-templates.md)
<!-- TOC: 1 Acknowledging Task Assignment from AMCOS/AMAMA | 2 Delegating Task to Sub-Agent | 3 Requesting Status Update from Sub-Agent | 4 Reporting Task Completion to AMCOS | 5 Escalating Blocked Task to AMCOS | 6 Escalating Blocked Task to AMAMA (User Decision Needed) | 7 Standard AI Maestro API Format and Conventions | Quick Reference: Common Patterns | Notes | Decision Trees for AI Maestro Message Handling -->
## Error Handling
On failure, retry once then escalate per [references/escalation-protocol.md](references/escalation-protocol.md)
<!-- TOC: Escalation Order | State-Based Triggers | Priority Escalation | Important Notes -->
See also: [references/error-handling-quickref.md](references/error-handling-quickref.md)
<!-- TOC: Error Handling | Quick Reference Card -->
## Examples
See: [references/examples.md](references/examples.md)
<!-- TOC: Full Task Assignment Flow | Example 1: Send Task Assignment | Example 2: Send Status Request | Example 3: Escalate to Assistant Manager -->
**Input:** Send task assignment to agent via `agent-messaging` skill with scenario=task_assignment, to=agent-name, subject="Run tests"
**Output:** `{"status":"sent","message_id":"msg-12345"}`
## Output
JSON messages, API confirmations with message_id, and markdown delegation log entries.
## Resources
- **AGENT_OPERATIONS.md**, **amoa-label-taxonomy**, **amoa-task-distribution**, **amoa-progress-monitoring**Related Skills
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