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khanhbkqt/spawn-agent

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A skill for Antigravity that delegates scoped work to Gemini CLI or Codex CLI worker agents — keeping the main context clean.

Overview

Antigravity doesn't natively support spawning sub-agents. This skill fills that gap — use Gemini CLI or Codex CLI as worker agents to handle implementation, research, and bug fixes while the orchestrator stays focused. Antigravity is powerful, but it has no built-in way to delegate work to sub-agents. Every file read, build output, and error trace goes into the same context window — and it fills up fast. Once it does, the agent loses track of earlier instructions and can't reason about the big picture. The main agent acts as an — it plans, delegates, and reviews. Worker agents (Gemini or Codex) handle the actual implementation in isolated sessions. At least one of these CLI tools must be installed: Clone into your Antigravity skills directory: Antigravity will automatically discover the skill from SKILL.md and learn the delegation protocol. Choose the agent based on the task — don't be loyal to one CLI. Each has its own strengths.

README


The Problem

Antigravity is powerful, but it has no built-in way to delegate work to sub-agents. Every file read, build output, and error trace goes into the same context window — and it fills up fast. Once it does, the agent loses track of earlier instructions and can’t reason about the big picture.

Before spawn-agent:

Main Agent Context:
├── User conversation          ~5%
├── Codebase understanding     ~10%
├── File A contents            ~15%  ← polluting
├── File B contents            ~15%  ← polluting
├── Build output               ~20%  ← polluting
├── Lint errors                ~10%  ← polluting
└── Remaining for reasoning    ~25%  ← squeezed

After spawn-agent:

Main Agent Context (Orchestrator):         Worker Agent Context:
├── User conversation     ~15%             ├── Task prompt          ~10%
├── Codebase overview     ~20%             ├── File A contents      ~25%
├── Delegation plan       ~10%             ├── File B contents      ~25%
├── Worker results        ~15%             ├── Build output         ~20%
└── Remaining reasoning   ~40%  ← clean   └── Implementation       ~20%

How It Works

The main agent acts as an orchestrator — it plans, delegates, and reviews. Worker agents (Gemini or Codex) handle the actual implementation in isolated sessions.

Orchestrator                    Worker (Gemini/Codex)
     │                               │
     ├──── 1. DEFINE task ────────►   │
     ├──── 2. COMPOSE prompt ─────►   │
     ├──── 3. SPAWN ──────────────►   ├── reads codebase
     │                                ├── implements changes
     │                                ├── runs verification
     │     ◄── 4. OUTPUT ────────────┘
     ├──── 5. REVIEW results
     └──── 6. REPORT to user

Installation

Prerequisites

At least one of these CLI tools must be installed:

# Gemini CLI
npm install -g @google/gemini-cli

# Codex CLI
npm install -g @openai/codex

Install the Skill

Clone into your Antigravity skills directory:

# Recommended: into your global skills directory
git clone https://github.com/khanhbkqt/spawn-agent.git ~/.gemini/antigravity/skills/spawn-agent

# Or per-project
git clone https://github.com/khanhbkqt/spawn-agent.git .agent/skills/spawn-agent

# Or symlink from a central location
git clone https://github.com/khanhbkqt/spawn-agent.git ~/spawn-agent
ln -s ~/spawn-agent ~/.gemini/antigravity/skills/spawn-agent

Make the script executable:

chmod +x ~/.gemini/antigravity/skills/spawn-agent/scripts/spawn-agent.sh

Antigravity will automatically discover the skill from SKILL.md and learn the delegation protocol.

Quick Start

1. Simple inline task

./scripts/spawn-agent.sh --gemini --yolo -p "Count all TODO comments in src/ and list them"

2. Complex task with a template

Create a prompt file from a template:

cp templates/implementation-task.md /tmp/spawn-agent-task-auth.md
# Fill in the template sections...

Then spawn:

./scripts/spawn-agent.sh --codex --auto-edit --timeout 300 -f /tmp/spawn-agent-task-auth.md

3. Read-only research

./scripts/spawn-agent.sh --gemini --yolo --timeout 120 \
  -p "Analyze the authentication flow in packages/backend/src/auth/. 
      List all JWT-related functions and their dependencies.
      Output as a markdown summary. DO NOT modify any files."

Choosing an Agent

Agent CLI Strengths Best for
Gemini gemini Fast, good at codebase understanding, reads project context Research, context gathering, quick implementations
Codex codex exec Strong reasoning, sandboxed execution, code review capability Complex implementation, refactoring, bug fixing

Tip: Choose the agent based on the task — don’t be loyal to one CLI. Each has its own strengths.

Approval Modes

Mode Flag Gemini Codex
Auto-edit --auto-edit auto_edit auto-edit
Full auto --yolo yolo full-auto
Safest --safe default suggest

Templates

Three prompt templates are provided for common task types:

Task Type Template When to Use
Implementation implementation-task.md Adding features, building modules, refactoring
Research research-task.md Codebase analysis, context gathering (read-only)
Bug Fix bugfix-task.md Targeted fixes with known or suspected location

Each template includes sections for goal, scope, constraints, and expected output format. Fill in all sections before delegating — headless workers can’t ask clarifying questions.

Quick inline format (for simple tasks)

# Task: 
## Goal: 
## Files: 
## Constraints: DO NOT modify files outside 
## When done: Summarize changes made and any issues found.

When to Use (and When Not To)

Use spawn-agent when:

  • Implementation task has a clear scope (fix bug, add function, refactor file)
  • You need to research/query the codebase without polluting the main context
  • The task is independent and doesn’t need intermediate human review
  • You want to keep the main context clean for high-level reasoning

Don’t use when:

  • Task requires interactive discussion with the user
  • Scope is too broad (refactoring an entire module)
  • Multiple files with complex inter-dependencies need coordination
  • Task needs browser interaction or external API calls

Anti-Patterns

❌ Don’t ✅ Do
Delegate too broadly: “Refactor the entire backend” Scope it: “Refactor auth.service.ts to extract token logic into token.service.ts”
Skip constraints — agent may modify files outside scope Set boundaries: “DO NOT modify files outside packages/backend/src/auth/”
Spawn and assume success Always review: read output, verify changes, check errors
Chain delegates: A → output feeds B → … Orchestrator controls flow: read result A, decide, then spawn B if needed

Script Reference

Usage: spawn-agent.sh [options]

Agent Selection:
  --gemini                Use Gemini CLI (default)
  --codex                 Use Codex CLI

Prompt:
  -p, --prompt TEXT       Prompt text (inline)
  -f, --file PATH         Prompt file (markdown)

Approval Modes:
  --yolo                  Auto-approve everything
  --auto-edit             Auto-approve edits only (default)
  --safe                  Prompt for every action

Other:
  --timeout SECONDS       Max execution time (default: 300)
  --output PATH           Custom output file path
  -h, --help              Show this help

Compatibility

Built for Antigravity (Google DeepMind), but works with any AI coding assistant that reads SKILL.md files:

  • Antigravity — ~/.gemini/antigravity/skills/ (primary target)
  • Claude Code (Anthropic) — .agent/skills/
  • Gemini CLI (Google) — .gemini/skills/
  • Cursor — via rules or skills directories
  • Any agent that supports Markdown-based skill definitions

Contributing

See CONTRIBUTING.md for guidelines.

License

MIT

View this README on GitHub

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Install

npx skillfish add khanhbkqt/spawn-agent