OpenClaw QuickStart (4): Configuration, Model Providers, and the Coding Plan Trick

If you only edit one file in OpenClaw, this is it.

~/.openclaw/openclaw.json controls models, tools, channels, memory, cron, and skill loading. The onboarding wizard wrote a default; this piece walks the parts you will actually touch.

The minimal viable config

Strip away the comments and the default sets, and a working config is about 25 lines:

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{
  "agent": {
    "name": "Lobster",
    "default_model": "qwen-plus"
  },
  "providers": {
    "dashscope": {
      "api_key": "sk-...",
      "models": ["qwen-turbo", "qwen-plus", "qwen3-max", "qwen3-coder-plus"]
    }
  },
  "tools": {
    "exec": { "trusted_patterns": ["^ls ", "^cat ", "^echo "] },
    "web_search": { "engine": "bing" }
  },
  "memory": {
    "engine": "semantic",
    "max_tokens_per_turn": 2000
  }
}

Five sections. Let’s go through them in order.

agent — name and default model

Two fields matter: the name (what the user sees) and the default model. Default model is what the agent uses for the planning loop unless a tool or skill overrides it.

The mistake people make is putting the most expensive model here, “to be safe.” Don’t. The planning loop runs on every turn. Put qwen-plus here, and override to qwen3-max only inside specific skills that need real reasoning.

providers — where the models live

You can configure multiple providers and pick per-skill. The four useful options:

The Coding Plan is genuinely interesting — see below.

The Coding Plan trick

Aliyun Bailian has a “Coding Plan” subscription: 200元 per month gets you eight models — Claude Sonnet 4.5, Qwen3-Max, Qwen3-Coder-Plus, DeepSeek V3.1, GLM-4.6, and more — at unmetered usage during business hours. This is wildly underpriced for an agent that loops a few hundred times per day.

The provider config is one block:

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"bailian-coding-plan": {
  "endpoint": "https://dashscope.aliyuncs.com/coding-plan/v1",
  "api_key": "sk-..."  // your Coding Plan key, not the regular DashScope one
}

Then in agent.default_model, just point at one of the model IDs the plan exposes (claude-sonnet-4-5, qwen3-max, etc.) and the requests are billed against your subscription.

I would not recommend the Coding Plan if you are running OpenClaw on a single laptop for personal use — DashScope’s free tier is enough. I would absolutely recommend it if you are running anything with cron jobs or multiple channels.

tools — turning sharp things on

Two tool configs are worth tuning:

exec.trusted_patterns — regexes that bypass the per-call confirmation. I keep mine narrow: read-only commands like ls, cat, git status. Anything that mutates the filesystem stays gated.

web_search.engine — bing (cheap, decent), serper (better quality, costs), or tavily (best for agentic search, costs more). I default to bing and let the agent ask if it needs better.

There are 24 other tools. Most of them have sensible defaults. The ones I have edited:

• read.max_bytes — bumped from 50KB to 500KB so the agent can swallow a config file.
• write.allowed_paths — restricted to ~/openclaw-workspace/ and ~/Documents/. This is the single most useful safety setting.

memory — how the agent remembers

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"memory": {
  "engine": "semantic",
  "max_tokens_per_turn": 2000,
  "auto_write": true,
  "types": ["user", "project", "reference", "feedback"]
}

max_tokens_per_turn is the budget for memory snippets in each prompt. Default is 1000. I bump to 2000 because skills already eat tokens; if memory is too small, the agent forgets.

auto_write lets the agent decide when to commit something to memory. With this off you have to say “remember that I prefer Python over Node” explicitly. With it on, the agent infers. I leave it on and accept the occasional spurious memory.

channels — wired up later

Empty by default. The next piece in this series adds Telegram. The skeleton looks like:

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"channels": {
  "telegram": {
    "enabled": true,
    "bot_token": "...",
    "allowed_user_ids": [123456789]
  }
}

The allowed_user_ids field is non-optional in spirit — without it your bot answers anyone who finds it. Don’t ship without it.

cron — scheduled jobs

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"cron": {
  "jobs": [
    {
      "name": "daily-briefing",
      "schedule": "0 7 * * *",
      "skill": "daily-briefing"
    }
  ]
}

This is the feature that turns OpenClaw from “a chatbot” into “a thing that quietly does work for you.” A cron entry triggers a skill; the skill produces output; the output is sent to a default channel (or whichever channel the skill specifies). The morning briefing case study is built on this.

Reload after editing

Most of openclaw.json is hot-reloaded on save. The exceptions are channel registrations and provider keys — for those, restart the gateway:

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openclaw gateway restart

If you ever see “tool not registered” or “provider not found” after editing, that’s the cue.

What I would change in your config today

If you onboarded with the wizard and haven’t touched the file:

1. Set tools.write.allowed_paths to something explicit. The default is your home directory and that is too broad.
2. Set memory.max_tokens_per_turn to 2000.
3. If you are anywhere near 200元/month of token spend, switch to the Bailian Coding Plan.

Next piece, channels. We wire up Telegram first because it’s painless, then take a single screenshot tour of WeChat WorkBuddy because it deserves its own day.