Agent-team-manager

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name: ai-agent-team-manager description: Professional AI agent team management system for coordinating multiple OpenClaw agents. Implements the proven Otter Camp methodology with task assignment, progress tracking, quality control, and performance evaluation. metadata: openclaw: requires: env: - OPENCLAW_WORKSPACE bins: - git - node - python3

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AI Agent Team Manager

Overview

This skill implements a professional AI agent team management system based on the Otter Camp methodology. It enables you to coordinate multiple OpenClaw agents working together on complex projects with proper task assignment, progress tracking, quality control, and performance evaluation.

When to Use This Skill

Use this skill when you need to:

Manage multiple AI agents working on the same project

Implement structured workflows for complex tasks

Track progress and ensure quality across agent teams

Evaluate agent performance and optimize workflows

Scale AI operations beyond single-agent capabilities

Core Features

Task Assignment & Coordination

Intelligent task decomposition and assignment

Agent role definition and specialization

Dependency management between tasks

Resource allocation and load balancing

Progress Tracking & Monitoring

Real-time progress dashboards

Milestone tracking and deadline management

Automated status reporting

Issue detection and escalation

Quality Control & Review

Multi-layer quality assurance processes

Peer review between agents

Human-in-the-loop checkpoints

Automated testing and validation

Performance Evaluation

Agent performance metrics and scoring

Workflow optimization recommendations

Cost-benefit analysis of agent configurations

Continuous improvement through learning

Usage Examples

Basic Team Setup

const teamManager = new AIAgentTeamManager({
  workspace: '/path/to/workspace',
  agents: ['xiaolv', 'laogou', 'xiaoqiu', 'xiaozhu'],
  methodology: 'otter-camp'
});

Task Coordination

await teamManager.assignTask({
  taskId: 'email-analysis-2026',
  description: 'Analyze 3,418 emails from QQ mailbox',
  assignee: 'xiaolv',
  reviewers: ['laogou'],
  deadline: '2026-03-10',
  qualityChecks: ['accuracy', 'completeness', 'formatting']
});

Performance Reporting

const report = await teamManager.generatePerformanceReport({
  period: 'last-30-days',
  metrics: ['tasksCompleted', 'qualityScore', 'efficiency', 'cost']
});

Integration Points

Works seamlessly with existing OpenClaw agents

Integrates with Git for version control

Supports custom agent roles and specializations

Compatible with all OpenClaw skill types

Best Practices

Start with small teams (2-4 agents) and scale gradually

Implement regular quality reviews and checkpoints

Use human oversight for critical decisions

Continuously optimize based on performance data

Maintain clear documentation of team workflows

Security & Compliance

All data remains in your local workspace

No external API calls without explicit permission

Full audit trail of all agent activities

Compliant with enterprise security requirements

Start with small teams (2-4 agents) and scale gradually

Implement regular quality reviews and checkpoints

Use human oversight for critical decisions

Continuously optimize based on performance data

Maintain clear documentation of team workflows