"
```
Go to Telegram
1. Open you-bot
2. Send "Hi"
3. Getting a pairing code "XXXXX"
Go to OpenClaw CLI
```bash
docker compose run --rm openclaw-cli pairing list telegram
docker compose run --rm openclaw-cli pairing approve telegram XXXXX
```
Done
##### Bot Commands
- `/btw` : 題外話，在不打斷目前對話（主任務），可以臨時問一個小問題，其內容不會進入主對話的上下文。
- `/subagent` : 子代理，在不打斷目前對話（主任務），呼叫另一個代理執行其他任務，其任務結果會納入主任務的上下文。
- `/new` : 新對話，建立新的對話（任務），全新的上下文，可節省 Token 用量。
#### Gateway
##### Local only (default)
- 遠端存取可以使用 SSH Port Forwarding
`~/.openclaw/openclaw.json` :
```json
"gateway": {
"port": 18789,
"mode": "local",
"bind": "loopback",
"controlUi": {
"allowedOrigins": [
"http://localhost:18789",
"http://127.0.0.1:18789"
]
},
"auth": {
"mode": "token",
"token": "YOUR-OPENCLAW-TOKEN"
},
```
##### Tailscale
openclaw.json 的 tailscale 功能不適用在 Docker 環境。
1. Tailscale Console: Enable **HTTPS Certicficates**
2. OpenClaw Host: Run
1. `sudo tailscale serve --bg --https=443 127.0.0.1:18789`
2. `tailscale serve status`
3. Change `~/.openclaw/openclaw.json` as follows
4. Connect to tailnet, and then visit https://your-openclaw-device.tailnet-domain/?token=YOUR-TOKEN , such as *https://dockers-vm.tailcb58c9.ts.net/* ?token=YOUR-TOKEN
`~/.openclaw/openclaw.json` :
- mode: local
- bind: loopback
- trustedProxies: \["127.0.0.1", "::1"\]
- allowedOrigins: https://yourdevice.tailnet-domain
```json
"gateway": {
"port": 18789,
"mode": "local",
"bind": "loopback",
"trustedProxies": ["127.0.0.1", "::1"],
"controlUi": {
"allowedOrigins": [
"http://localhost:18789",
"http://127.0.0.1:18789",
"https://yourdevice.tailnet-domain"
]
},
"auth": {
"mode": "token",
"token": "YOUR-OPENCLAW-TOKEN"
},
```
openclaw.json 的 tailscale 模式比較（不適用在 Docker 環境）
| 模式 | 存取範圍 | HTTPS | 認證 | 適用場景 |
| serve | 限 tailnet | 自動 | Tailscale identity headers/Token/Password | 個人使用 |
| funnel | 公眾網路 | 自動 | Password | Webhook |
| bind: "tailnet" | 限 tailnet | 無 | Token/Password | 低延遲 |
| off | 限 localhost | 無 | Token | SSH Port Forward |
#### Skill
##### 3rd Party
- [Architecture Diagram Generator](https://github.com/Cocoon-AI/architecture-diagram-generator): 繪製架構圖並輸出 HTML 格式。
- [Khazix Skills](https://github.com/KKKKhazix/khazix-skills): 橫縱分析法深度研究。
#### FAQ
##### Context limit exceeded
> Context limit exceeded. I've reset our conversation to start fresh - please try again.
>
> To prevent this, increase your compaction buffer by setting agents.defaults.compaction.reserveTokensFloor to 20000 or higher in your config.
Cause: 目前使用模型的 Context Window 與 壓縮緩衝參數不匹配。
Solution: 以 Gemma4-31B-it 為例
Edit: ~/.openclaw/openclaw.json
- `contextWindow` : 128000
- `reserveTokensFloor` : 40000
```json
"models": {
"mode": "merge",
"providers": {
"custom-cpamc": {
"baseUrl": "http://192.168.31.89:8317/v1",
"api": "openai-completions",
"apiKey": "sk-cvgaT1Z3EhJRBB5pu",
"models": [
{
"id": "gemma-4-31b-it",
"name": "gemma-4-31b-it (Custom Provider)",
"contextWindow": 128000,
"maxTokens": 4096,
"input": [
"text"
],
```
```json
"agents": {
"defaults": {
"workspace": "/home/alang/.openclaw/workspace",
"model": {
"primary": "custom-cpamc/gemma-4-31b-it"
},
"models": {
"custom-cpamc/gemma-4-31b-it": {}
},
"compaction": {
"reserveTokensFloor": 40000
}
}
},
```
或者使用 CLI
```bash
openclaw config set agents.defaults.compaction.reserveTokensFloor 40000
```
##### LLM idle timeout
> The model did not produce a response before the LLM idle timeout. Please try again, or increase agents.defaults.llm.idleTimeoutSeconds in your config (set to 0 to disable).
Solution:
```bash
openclaw config set agents.defaults.timeoutSeconds 600
openclaw config set agents.defaults.llm.idleTimeoutSeconds 600
```
##### gateway connect failed
> gateway connect failed: GatewayClientRequestError: pairing required
檢查有無 pending devices
```bash
openclaw devices list
openclaw devices list --json
```