amoa-progress-monitoring

Use when monitoring agent progress. Trigger with status check or stall detection requests. Loaded by ai-maestro-orchestrator-agent-main-agent

7 stars

Best use case

amoa-progress-monitoring is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Use when monitoring agent progress. Trigger with status check or stall detection requests. Loaded by ai-maestro-orchestrator-agent-main-agent

Teams using amoa-progress-monitoring 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

$curl -o ~/.claude/skills/amoa-progress-monitoring/SKILL.md --create-dirs "https://raw.githubusercontent.com/Emasoft/ai-maestro-orchestrator-agent/main/skills/amoa-progress-monitoring/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/amoa-progress-monitoring/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How amoa-progress-monitoring Compares

Feature / Agentamoa-progress-monitoringStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Use when monitoring agent progress. Trigger with status check or stall detection requests. 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

# Progress Monitoring Skill

## Overview

Monitors agent progress via state transitions, detects stalls, and escalates issues.

## Prerequisites

Requires **AGENT_OPERATIONS.md**, **amoa-label-taxonomy**, **amoa-messaging-templates**, AI Maestro API, GitHub CLI.

## Instructions

States: Acknowledged, No ACK, Active, No Progress, Stale, Unresponsive, Blocked, Complete. Transitions: Assigned→Acknowledged→Active→Complete. Stalls: No Progress→Stale→Unresponsive.
<!-- TOC: Escalation|Reminders|Reassignment|Progress|Completion -->

1. Query `status:in-progress` issues; determine each agent's state via timestamps
2. No ACK/No Progress/Stale → send reminder or status request
3. Unresponsive → escalate; Blocked → create `type:blocker` issue, notify user
4. Complete → verify PR, tests, review, docs; update labels
<!-- TOC: IronRule|BlockerDef|Protocol|Labels|Resolution|Lifecycle -->

Copy this checklist and track your progress:

- [ ] Query in-progress issues and determine agent states
- [ ] Send reminders/escalate as needed per state
- [ ] Verify completions and update labels

## Output

State report table (task, agent, state, last update) + escalation messages + blocker issues.

## Examples

**Input:** Query state for task #42 assigned to `libs-svg-svgbbox`
**Output:** `| #42 | libs-svg-svgbbox | Stale | 2h ago |` → sends status request

## Error Handling

Escalate: reminder→urgent→reassignment. Blockers→`type:blocker` issues. See [references/monitoring-examples.md](references/monitoring-examples.md).
<!-- TOC: Example 1: Query Agent State via AI Maestro | Example 2: Send First Reminder | Example 3: Escalate to Urgent | Example 4: Handle Blocker Report | Example 5: Verify Completion | Dashboard Queries | Error Handling -->

## Resources

- [references/blocker-handling-protocol.md](references/blocker-handling-protocol.md)
  - Iron Rule for Blockers
  - Comprehensive Blocker Definition
  - Blocker Response Protocol
  - Update Labels and Create Blocker Issue
  - Resolution
  - When Blocker Resolved
  - Blocker Lifecycle Checklist
- [references/escalation-and-messaging.md](references/escalation-and-messaging.md)
  - Escalation Order
  - First Reminder
  - Urgent Reminder
  - Reassignment Decision
  - Progress Report Format
    - Status Update
    - Completion Report
    - Blocker Report
  - Completion Verification
    - Verification Checklist
    - If Verification Passes
    - If Verification Fails
- [references/monitoring-examples.md](references/monitoring-examples.md)
  - Example 1: Query Agent State via AI Maestro
  - Example 2: Send First Reminder
  - Example 3: Escalate to Urgent
  - Example 4: Handle Blocker Report
  - Example 5: Verify Completion
  - Dashboard Queries
  - Error Handling

Related Skills

amoa-verification-patterns

7
from Emasoft/ai-maestro-orchestrator-agent

Use when verifying implementations. Trigger with verification, testing, or evidence requests. Loaded by ai-maestro-orchestrator-agent-main-agent

amoa-two-phase-mode

7
from Emasoft/ai-maestro-orchestrator-agent

Use when running Plan-then-Execute workflows. Trigger with plan-execute or two-phase requests. Loaded by ai-maestro-orchestrator-agent-main-agent

amoa-task-distribution

7
from Emasoft/ai-maestro-orchestrator-agent

Use when distributing tasks. Trigger with task assignment requests. Loaded by ai-maestro-orchestrator-agent-main-agent

amoa-remote-agent-coordinator

7
from Emasoft/ai-maestro-orchestrator-agent

Use when coordinating remote AI agents via AI Maestro messaging. NOT for human coordination. Trigger with agent delegation or multi-agent requests. Loaded by ai-maestro-orchestrator-agent-main-agent

amoa-plan-phase

7
from Emasoft/ai-maestro-orchestrator-agent

Use when running Plan Phase of two-phase mode. Trigger with planning, requirements, or plan approval requests. Loaded by ai-maestro-orchestrator-agent-main-agent

amoa-orchestration-patterns

7
from Emasoft/ai-maestro-orchestrator-agent

Use when breaking down tasks for human developers. Trigger with task decomposition requests. Loaded by ai-maestro-orchestrator-agent-main-agent

amoa-orchestration-loop

7
from Emasoft/ai-maestro-orchestrator-agent

Use when running the orchestrator loop or managing stop hook behavior. Trigger with loop, stop hook, or state file requests. Loaded by ai-maestro-orchestrator-agent-main-agent

amoa-module-sync

7
from Emasoft/ai-maestro-orchestrator-agent

Use when syncing modules with GitHub Issues or troubleshooting module state. Trigger with sync, issue, or module troubleshooting requests. Loaded by ai-maestro-orchestrator-agent-main-agent

amoa-module-management

7
from Emasoft/ai-maestro-orchestrator-agent

Use when managing modules during Orchestration Phase. Trigger with module add, modify, or reassign requests. Loaded by ai-maestro-orchestrator-agent-main-agent

amoa-module-lifecycle

7
from Emasoft/ai-maestro-orchestrator-agent

Use when adding, modifying, removing, prioritizing, or reassigning modules. Trigger with module CRUD requests. Loaded by ai-maestro-orchestrator-agent-main-agent

amoa-messaging-templates

7
from Emasoft/ai-maestro-orchestrator-agent

Use when sending inter-agent messages. Trigger with task assignment, status report, or escalation needs. Loaded by ai-maestro-orchestrator-agent-main-agent

amoa-label-taxonomy

7
from Emasoft/ai-maestro-orchestrator-agent

Use when applying GitHub labels. Trigger with label query or assignment requests. Loaded by ai-maestro-orchestrator-agent-main-agent