# Launch Sub Agent

Launch an intelligent sub-agent with automatic model selection based on task...

- Repository: https://github.com/NeoLabHQ/context-engineering-kit (1797 stars)
- Category: AI and agents
- License: GPL-3.0
- Last updated: 2026-08-26
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add NeoLabHQ/context-engineering-kit --skill launch-sub-agent -g -a claude-code -y`
Codex: `npx skills add NeoLabHQ/context-engineering-kit --skill launch-sub-agent -g -a codex -y`
Cursor: `npx skills add NeoLabHQ/context-engineering-kit --skill launch-sub-agent -g -a cursor -y`
Gemini CLI: `npx skills add NeoLabHQ/context-engineering-kit --skill launch-sub-agent -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add NeoLabHQ/context-engineering-kit`

## Description

Launch an intelligent sub-agent with automatic model selection based on task complexity, specialized agent matching, Zero-shot CoT reasoning, and mandatory self-critique verification

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# launch-sub-agent

<task>
Launch a focused sub-agent to execute the provided task. Analyze the task to intelligently select the optimal model and agent configuration, then dispatch a sub-agent with Zero-shot Chain-of-Thought reasoning at the beginning and mandatory self-critique verification at the end.
</task>

<context>
This command implements the **Supervisor/Orchestrator pattern** from multi-agent architectures where you (the orchestrator) dispatch focused sub-agents with isolated context. The primary benefit is **context isolation** - each sub-agent operates in a clean context window focused on its specific task without accumulated context pollution.
</context>

## Process

### Phase 1: Task Analysis with Zero-shot CoT

Before dispatching, analyze the task systematically. Think through step by step:

```
Let me analyze this task step by step to determine the optimal configuration:

1. **Task Type Identification**
   "What type of work is being requested?"
   - Code implementation / feature development
   - Research / investigation / comparison
   - Documentation / technical writing
   - Code review / quality analysis
   - Architecture / system design
   - Testing / validation
   - Simple transformation / lookup

2. **Complexity Assessment**
   "How complex is the reasoning required?"
   - High: Architecture decisions, novel problem-solving, multi-faceted analysis
   - Medium: Standard implementation following patterns, moderate research
   - Low: Simple transformations, lookups, well-defined single-step tasks

3. **Output Size Estimation**
   "How extensive is the expected output?"
   - Large: Multiple files, comprehensive documentation, extensive analysis
   - Medium: Single feature, focused deliverable
   - Small: Quick answer, minor change, brief output

The rest: https://github.com/NeoLabHQ/context-engineering-kit/blob/HEAD/antigravity/skills/launch-sub-agent/SKILL.md