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komong

Agent-team-manager

by komong · GitHub ↗ · v1.0.0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install 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, pr...
README (SKILL.md)

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
Usage Guidance
Do not deploy this skill to production yet. The package has several internal inconsistencies that make its real behavior unclear: package.json points to index.js but index.js is missing; example code requires './index' but no entrypoint is present; the metadata lists python3 as a required binary although the code is JavaScript; OPENCLAW_WORKSPACE is declared required but isn’t referenced in the visible source. What to do before installing: 1) Ask the author/source for the missing index.js and a clear install/run procedure and confirm why python3 is required. 2) Inspect the missing/omitted files and any entrypoint to ensure there are no network calls or credential reads (search for process.env, http/https, net, child_process, fetch). 3) Run the code in an isolated sandbox/container and verify behavior (no unexpected outbound connections, no filesystem access outside the intended workspace). 4) Only provide workspace paths that do not expose sensitive data, and do not supply secrets or cloud credentials. 5) Prefer packages with a verifiable homepage, tests, and a clear entrypoint; if the author cannot provide the missing pieces and a clear explanation, treat the skill as untrusted.
Capability Analysis
Type: OpenClaw Skill Name: ai-agent-team-manager Version: 1.0.0 The bundle provides a comprehensive framework for multi-agent coordination, including task allocation, quality control, and performance tracking based on the 'Otter Camp' methodology. Analysis of the JavaScript modules (e.g., workflow-manager.js, quality-controller.js) and documentation reveals no evidence of malicious intent, data exfiltration, or unauthorized command execution. The code consists of standard state management logic and boilerplate for agent orchestration, and its behavior is entirely consistent with the stated purpose of managing AI agent teams.
Capability Assessment
Purpose & Capability
Name/description (agent team management) matches the included JS modules (task allocation, tracking, quality, performance). However metadata and files diverge: package.json declares main: "index.js" but no index.js is present in the file manifest; example usage requires './index'. The manifest lists many JS modules but no entrypoint/exports, so it's unclear how the package is intended to be executed or integrated. Declared binary requirement 'python3' is not justified by the provided JavaScript source. These mismatches reduce confidence that required items are proportionate to the stated purpose.
Instruction Scope
SKILL.md describes local-only operation, Git integration, and workspace-based operation; its usage examples pass workspace paths explicitly. The SKILL.md's runtime instructions do not ask the agent to read unrelated system files or exfiltrate secrets. However the doc declares OPENCLAW_WORKSPACE as required env but the visible code does not reference process.env.OPENCLAW_WORKSPACE (no file in the included snippets uses that env), and example tasks mention analyzing an external QQ mailbox — an integration not implemented in the visible code. The instructions are generally scoped to team-management tasks but give the agent some latitude (e.g., 'works with Git') without concrete implementation details.
Install Mechanism
No install specification is provided (instruction-only), which is low risk, but the bundle actually contains multiple source files and a publish.sh. The presence of code + package.json without an install/build spec or entrypoint is an inconsistency. There is no remote download or extract step flagged. Overall installation behavior is unclear because required runtime binaries are declared but no install script uses them; that unpredictability is worth caution.
Credentials
Declared required env var: OPENCLAW_WORKSPACE (reasonable for a workspace-based manager). But the provided code snippets do not reference process.env.OPENCLAW_WORKSPACE or other environment variables, suggesting a mismatch between declared requirements and actual behavior. Declared required binaries include python3, but visible code is Node.js and does not call Python; git is listed (SKILL.md says it integrates with Git) but the code does not show git invocation. This disparity could indicate incomplete packaging or inaccurate metadata — both reduce transparency and raise risk because the real runtime needs aren't verifiable from the bundle.
Persistence & Privilege
Skill does not request always:true and does not claim to modify other skills or system-wide settings. No install spec attempts to create persistent system services. The code shown performs in-memory data management and logging; there are no obvious attempts to persist credentials or change agent configuration beyond its own structures.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install ai-agent-team-manager
  3. After installation, invoke the skill by name or use /ai-agent-team-manager
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of ai-agent-team-manager implementing the Otter Camp methodology for managing multiple OpenClaw agents. - Features intelligent task assignment, real-time progress tracking, and structured quality control processes. - Enables agent performance evaluation with metrics, workflow optimization, and reporting. - Supports seamless integration with OpenClaw agents, Git for version control, and customizable agent roles. - Includes strong data security and compliance features with local data storage and audit trails.
Metadata
Slug ai-agent-team-manager
Version 1.0.0
License
All-time Installs 1
Active Installs 1
Total Versions 1
Frequently Asked Questions

What is Agent-team-manager?

Professional AI agent team management system for coordinating multiple OpenClaw agents. Implements the proven Otter Camp methodology with task assignment, pr... It is an AI Agent Skill for Claude Code / OpenClaw, with 413 downloads so far.

How do I install Agent-team-manager?

Run "/install ai-agent-team-manager" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Agent-team-manager free?

Yes, Agent-team-manager is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Agent-team-manager support?

Agent-team-manager is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Agent-team-manager?

It is built and maintained by komong (@komong); the current version is v1.0.0.

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