agent-spawner

Create and delegate tasks to specialized agents for parallel GTM execution.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/GetFresh-Ventures/gxd-ceo-ai-kit --skill agent-spawner-getfresh-ventures
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-spawner
Source: https://github.com/GetFresh-Ventures/gxd-ceo-ai-kit/tree/main/skills/agent-spawner
Command: npx skills add https://github.com/GetFresh-Ventures/gxd-ceo-ai-kit --skill agent-spawner-getfresh-ventures

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Dynamically create and manage specialist agents to execute GTM tasks in parallel, reducing latency and coordination overhead across the GFV ecosystem.

Core Features & Use Cases

  • Dynamic agent creation and management for parallel task execution across GTM workflows.
  • Hierarchical topology with anti-drift controls to prevent agent divergence.
  • Agent types including Researcher, Analyst, Builder, Connector, and Auditor for specialized tasks.
  • Spawn protocol and coordination with a centralized coordinator for reliable outcomes.
  • Use cases include new client onboarding, multi-source data synthesis, cross-system reconciliation, and ongoing system health checks.

Quick Start

Describe the task context and let the Agent Spawner initialize parallel specialist agents.

Frequently Asked Questions about agent-spawner

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

FAQPage Schema
How do I orchestrate parallel GTM tasks across multiple data sources without losing coordination?▼

Parallel multi-agent orchestration works by dynamically creating specialized agents—such as Researchers and Analysts—under a centralized coordinator that uses a spawn decision matrix and anti-drift controls to prevent agent divergence during execution.

When do I need multi-agent orchestration for go-to-market workflows?▼

You need multi-agent orchestration when 3 or more data sources require querying, during new client onboarding, or when cross-system reconciliation is necessary across the GTM ecosystem to reduce latency and coordination overhead.

How to prevent agent drift when running parallel cross-system reconciliation tasks?▼

To prevent agent drift during cross-system reconciliation, implement hierarchical topology with anti-drift controls and coordinator-driven output validation, enforcing timeouts to ensure specialized agents stay aligned with the core task.

What specialized agent types are available for parallel GTM execution?▼

The specialized agent types available for parallel GTM execution include Researcher, Analyst, Builder, Connector, and Auditor, each designed to handle specific delegated tasks within the hierarchical orchestration topology.

Does multi-agent spawning work for ongoing system health checks and new client onboarding?▼

Yes, multi-agent spawning works for ongoing system health checks and new client onboarding by dynamically creating and delegating tasks to specialized agents for parallel execution, reducing overall latency and coordination overhead.