kickoff

Coordinate multi-agent meetings into a converged recommendation with structured reporting.

14|1|Updated Feb 20, 2026
One-click install
npx skills add https://github.com/pcatattacks/solopreneur-plugin --skill kickoff-pcatattacks
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: kickoff
Source: https://github.com/pcatattacks/solopreneur-plugin/tree/main/skills/kickoff
Command: npx skills add https://github.com/pcatattacks/solopreneur-plugin --skill kickoff-pcatattacks

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Orchestrates structured, collaborative agent meetings to gather diverse perspectives, challenge assumptions, and converge on a single, defensible recommendation.

Core Features & Use Cases

  • Team assembly: Selects the appropriate agent team based on task and context, with option for named or ad-hoc participants.
  • Phase-driven workflow: Manages Phase 0 (Team Selection), Phase 1 (Spawn Agent Team), and Phase 2 (Compile & Present), including task lists, prompts, and monitoring.
  • Structured reporting: Produces a formal kickoff report with consensus, debate points, key findings, and recommended next steps, then cleans up the meeting state.

Quick Start

Kick off a collaborative agent meeting on your topic by assembling the appropriate team and starting the phase 0 briefing.

Frequently Asked Questions about kickoff

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

FAQPage Schema
How do I run multi-agent meetings for collaborative analysis and decision-making?

Multi-agent meetings coordinate diverse perspectives by spawning agents for adversarial reviews and multi-perspective analysis. They enforce a phase-driven workflow to converge on a single, defensible recommendation with structured reporting and clear next steps.

What is the best way to get a defensible recommendation from multiple AI viewpoints?

Getting a defensible recommendation requires gathering diverse viewpoints to challenge assumptions. Adversarial reviews and collaborative problem solving converge multiple perspectives into a unified decision, documented in a formal report with consensus and debate points.

How does a phase-driven workflow manage team assembly for AI problem solving?

A phase-driven workflow manages team assembly across three stages: Phase 0 selects the agent team based on context, Phase 1 spawns agents and assigns prompts, and Phase 2 compiles findings and presents the final recommendation.

Can I select named participants or ad-hoc agents for multi-agent collaboration?

Multi-agent collaboration supports selecting both named participants and ad-hoc agents for team assembly. This flexibility ensures the appropriate agent team is chosen based on the specific task and context requirements.

Does multi-agent structured reporting include consensus and key findings?

Multi-agent structured reporting includes consensus, debate points, key findings, and recommended next steps. It produces a formal kickoff report after the collaborative analysis phase, then cleans up the meeting state.

When should I use adversarial reviews in collaborative problem solving?

Adversarial reviews should be used when collaborative problem solving requires diverse viewpoints to challenge assumptions. They are essential for tasks needing deep analysis to ensure final recommendations are defensible across multiple perspectives.