skills.rest
MomoDaviluke
MomoDavilukeCOMMUNITY
Explore all skills by this author →
GitHub

team-builder

Discover, select, and run multiple AI agents in parallel to synthesize unified reports.

2|Updated Mar 3, 2026
Search Tags:#workflow#orchestration#parallel#ai-agent#team#domain-discovery
One-click install
npx skills add https://github.com/MomoDaviluke/star-citizen-promotion --skill team-builder-momodaviluke
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: team-builder
Source: https://github.com/MomoDaviluke/star-citizen-promotion/tree/main/.agents/skills/ecc/team-builder
Command: npx skills add https://github.com/MomoDaviluke/star-citizen-promotion --skill team-builder-momodaviluke

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Coordinating multiple AI agents in parallel to form task-focused teams, enabling rapid, hands-off collaboration across domains.

Core Features & Use Cases

  • Dynamic discovery of agent prompts across a repository (flat and subdirectory layouts)
  • Domain-based selection, parallel spawning, and autonomous task execution
  • Parallel synthesis of agent outputs into a unified report with highlights of agreements and tensions
  • Use Case: quickly assemble an engineering and marketing team to audit a project and synthesize recommendations

Quick Start

Select domains or agents, provide a task description, and run the parallel agent team immediately.

Frequently Asked Questions about team-builder

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I coordinate multiple AI agents in parallel to form task-focused teams?▼

To coordinate multiple AI agents in parallel, you provide a task description and select domains, which triggers dynamic discovery and parallel spawning of expert agent teams for autonomous execution and unified synthesis.

Can I dynamically discover AI agent prompts across different repository layouts?▼

Yes, dynamic discovery of AI agent prompts is supported across both flat and subdirectory repository layouts, enabling non-hardcoded selection of domain-specific agent personas before parallel execution begins.

How does parallel AI agent orchestration synthesize outputs into a unified report?▼

Parallel AI agent orchestration synthesizes outputs by aggregating autonomous task results into a unified report, automatically highlighting areas of agreement and tension across diverse domain agents.

Do I need to hardcode agent personas to assemble an expert AI team on demand?▼

No, you do not need to hardcode agent personas; the system enforces non-hardcoded discovery, selecting domain-based agents dynamically to assemble teams for projects, site audits, or output synthesis.

How does this AI agent team orchestration handle failures during autonomous task execution?▼

During autonomous task execution, the orchestration system applies robust failure handling to manage errors across parallel agents, ensuring clean synthesis of final aggregated outputs despite individual agent issues.

What is the best way to assemble an engineering and marketing team to audit a project?▼

The best way to assemble an engineering and marketing team for a project audit is to select those specific domains, provide the audit task description, and run the parallel agent team for synthesized recommendations.

Related Skills

Explore More Software Engineering Skills→
KanakMalpaniKanakMalpani

team-builder

Orchestrate interactive agent selection and parallel execution for task-specific teams.

Community
Intermediate
zardusai-cyberzardusai-cyber
1

team-builder

Coordinates multiple expert agents to jointly tackle tasks and produce reports.

Community
Intermediate
zapabobzapabob
2

autonomous-orchestration-manager

Coordinates multi-agent workflows with task decomposition and token allocation.

Community
Advanced
luongldptitluongldptit

team-builder

Discover and run multiple AI agents in parallel, then synthesize their outputs into a unified report.

Community
Intermediate