agent-spawner

Spawn a new OpenClaw agent through conversation. Uses official Docker setup and non-interactive onboarding, carries over API keys, tools, plugins, and skills from the current agent. User answers 2-3 questions. Use when the user wants to create, spin up, deploy, or provision a new OpenClaw agent.

3,891 stars

Best use case

agent-spawner is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Spawn a new OpenClaw agent through conversation. Uses official Docker setup and non-interactive onboarding, carries over API keys, tools, plugins, and skills from the current agent. User answers 2-3 questions. Use when the user wants to create, spin up, deploy, or provision a new OpenClaw agent.

Teams using agent-spawner should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/agent-spawner/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/austineral/agent-spawner/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/agent-spawner/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How agent-spawner Compares

Feature / Agentagent-spawnerStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Spawn a new OpenClaw agent through conversation. Uses official Docker setup and non-interactive onboarding, carries over API keys, tools, plugins, and skills from the current agent. User answers 2-3 questions. Use when the user wants to create, spin up, deploy, or provision a new OpenClaw agent.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Agent Spawner

Deploy a new OpenClaw agent conversationally. Official install, carry over config from the current agent. User never edits a file.

## 1. Read Current Config (silent)

```bash
cat ~/.openclaw/openclaw.json
cat ~/.openclaw/.env 2>/dev/null
env | grep -iE 'API_KEY|TOKEN'
ls ~/.openclaw/extensions/
ls <workspace>/skills/
```

Identify:
- **Provider**: check `auth.profiles` in config — could be Anthropic, OpenAI, Gemini, custom, etc.
- **API key**: from env var or config (e.g. `ANTHROPIC_API_KEY`, `GEMINI_API_KEY`, `OPENAI_API_KEY`)
- **Model**: from `agents.defaults.model`
- **Tool keys**: anything in `tools.*` (search APIs, etc.)
- **Plugins**: `plugins.installs` — names and npm specs
- **Skills**: run `openclaw skills list` to see what's bundled vs workspace-only. Only carry over non-bundled skills.

## 2. Ask

1. **"Where should I deploy it?"** — Docker (local or remote SSH) or bare metal?
2. **"Name?"** — for container. Generate one if they don't care.
3. **"Anything special?"** — purpose, constraints. Optional.

Don't ask about keys, plugins, skills, ports, or config. Carry everything over, use defaults.

## 3. Confirm Plan

After gathering answers, present the full plan before doing anything. Show everything in one summary:

```
Here's the plan:

📦 Deploy: Docker on <target>
📛 Name: <agent-name>
🌐 Port: <port>

Carrying over from current agent:
  ✅ Provider: Anthropic (API key)
  ✅ Model: anthropic/claude-sonnet-4-20250514
  ✅ Brave Search API key
  ✅ Plugins: openclaw-agent-reach
  ✅ Skills: agent-spawner, weather
  ✅ Heartbeat: 30m

The new agent will bootstrap its own identity on first message.

Good to go?
```

Only list items that actually exist. Wait for explicit confirmation before proceeding. If the user wants changes, adjust and re-confirm.

## 4. Deploy

### Docker

```bash
git clone https://github.com/openclaw/openclaw.git <agent-name>
cd <agent-name>
```

Set env and run non-interactive onboard. Match the provider detected in step 1:

```bash
export OPENCLAW_IMAGE=alpine/openclaw:latest
export OPENCLAW_CONFIG_DIR=~/.openclaw-<agent-name>
export OPENCLAW_WORKSPACE_DIR=~/.openclaw-<agent-name>/workspace
export OPENCLAW_GATEWAY_PORT=<unused port, default 18789>
export OPENCLAW_GATEWAY_BIND=lan

mkdir -p $OPENCLAW_CONFIG_DIR/workspace
```

**Onboard flags vary by provider.** Use the matching `--auth-choice` and key flag:

| Provider | --auth-choice | Key flag |
|----------|--------------|----------|
| Anthropic | `apiKey` | `--anthropic-api-key` |
| Gemini | `gemini-api-key` | `--gemini-api-key` |
| OpenAI | `apiKey` | (set `OPENAI_API_KEY` env) |
| Custom | `custom-api-key` | `--custom-api-key` + `--custom-base-url` + `--custom-model-id` |

```bash
docker compose run --rm openclaw-cli onboard --non-interactive --accept-risk \
  --mode local \
  --auth-choice <detected> \
  --<provider>-api-key "$API_KEY" \
  --gateway-port 18789 \
  --gateway-bind lan \
  --skip-skills

docker compose up -d openclaw-gateway
```

Official compose uses **bind mounts** — host user owns files, no permission issues.

Onboard error about gateway connection is expected (not running yet). Config is written.

### Bare metal

```bash
curl -fsSL https://openclaw.ai/install.sh | bash -s -- --no-onboard

openclaw onboard --non-interactive --accept-risk \
  --mode local \
  --auth-choice <detected> \
  --<provider>-api-key "$API_KEY" \
  --gateway-port 18789 \
  --gateway-bind lan \
  --install-daemon \
  --daemon-runtime node \
  --skip-skills
```

## 5. Patch Running Agent

CLI alias:
- Docker: `OC="docker compose exec openclaw-gateway node /app/openclaw.mjs"`
- Bare metal: `OC="openclaw"`

**Config** (only patch what the current agent actually has):
```bash
$OC config set agents.defaults.model "<model>"
$OC config set agents.defaults.heartbeat.every "30m"
# Tool keys — only if they exist in current config
$OC config set tools.web.search.apiKey "<key>"
```

**Plugins** (from `plugins.installs` in current config):
```bash
$OC plugins install <npm-spec>
# Repeat for each plugin
```

**Skills** (copy workspace skills):
```bash
# Docker
docker cp <source-workspace>/skills/ <container>:/home/node/.openclaw/workspace/skills/
# Bare metal
cp -r <source-workspace>/skills/ ~/.openclaw/workspace/skills/
```

**Restart:**
```bash
docker compose restart openclaw-gateway  # Docker
openclaw gateway restart                 # bare metal
```

## 6. Hand Off

Read the gateway token:
```bash
grep -A1 '"token"' $OPENCLAW_CONFIG_DIR/openclaw.json
```

Tell the user:
- **URL:** `http://<host>:<port>/`
- **Token:** (from config — onboard auto-generates one)
- "Say hello — it'll bootstrap itself."

## Notes

- `openclaw` not in PATH inside Docker. Use `node /app/openclaw.mjs`.
- `--accept-risk` required for non-interactive onboard.
- `alpine/openclaw:latest` — pre-built official image.
- Don't use named Docker volumes — root ownership issues. Official compose uses bind mounts.
- Multiple agents on same host: use different `OPENCLAW_CONFIG_DIR` and `OPENCLAW_GATEWAY_PORT`.
- Plugins and skills persist in `~/.openclaw/` volume (extensions/ and workspace/skills/).
- SSH keys, git config, apt packages are ephemeral — not in the volume, by design.

Related Skills

---

3891
from openclaw/skills

name: article-factory-wechat

Content & Documentation

humanizer

3891
from openclaw/skills

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Content & Documentation

find-skills

3891
from openclaw/skills

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

General Utilities

tavily-search

3891
from openclaw/skills

Use Tavily API for real-time web search and content extraction. Use when: user needs real-time web search results, research, or current information from the web. Requires Tavily API key.

Data & Research

baidu-search

3891
from openclaw/skills

Search the web using Baidu AI Search Engine (BDSE). Use for live information, documentation, or research topics.

Data & Research

agent-autonomy-kit

3891
from openclaw/skills

Stop waiting for prompts. Keep working.

Workflow & Productivity

Meeting Prep

3891
from openclaw/skills

Never walk into a meeting unprepared again. Your agent researches all attendees before calendar events—pulling LinkedIn profiles, recent company news, mutual connections, and conversation starters. Generates a briefing doc with talking points, icebreakers, and context so you show up informed and confident. Triggered automatically before meetings or on-demand. Configure research depth, advance timing, and output format. Walking into meetings blind is amateur hour—missed connections, generic small talk, zero leverage. Use when setting up meeting intelligence, researching specific attendees, generating pre-meeting briefs, or automating your prep workflow.

Workflow & Productivity

self-improvement

3891
from openclaw/skills

Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.

Agent Intelligence & Learning

botlearn-healthcheck

3891
from openclaw/skills

botlearn-healthcheck — BotLearn autonomous health inspector for OpenClaw instances across 5 domains (hardware, config, security, skills, autonomy); triggers on system check, health report, diagnostics, or scheduled heartbeat inspection.

DevOps & Infrastructure

linkedin-cli

3891
from openclaw/skills

A bird-like LinkedIn CLI for searching profiles, checking messages, and summarizing your feed using session cookies.

Content & Documentation

notebooklm

3891
from openclaw/skills

Google NotebookLM 非官方 Python API 的 OpenClaw Skill。支持内容生成(播客、视频、幻灯片、测验、思维导图等)、文档管理和研究自动化。当用户需要使用 NotebookLM 生成音频概述、视频、学习材料或管理知识库时触发。

Data & Research

小红书长图文发布 Skill

3891
from openclaw/skills

## 概述

Content & Documentation