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OpenClaw Lark Robot API Interface Development

Lark's API ecosystem is massive — calendars, docs, sheets, messaging, approval flows, and more. The challenge isn't "can my OpenClaw bot call Lark APIs?" It's "how do I build a clean, maintainable API integration layer that doesn't turn into spaghetti code?"

Let's architect it properly.

The Integration Architecture

Your OpenClaw Lark bot sits between users and Lark's APIs. The key is building a modular API client that skills can share:

User Message → OpenClaw → Skill Router → API Client → Lark API
                                              ↓
                                        Response Formatter
                                              ↓
                                        User Response

Setting Up the Lark API Client

On your Tencent Cloud Lighthouse instance, create a reusable API client:

// /opt/clawdbot/lib/lark-api.js
const LARK_BASE = 'https://open.larksuite.com/open-apis';

class LarkAPIClient {
  constructor(appId, appSecret) {
    this.appId = appId;
    this.appSecret = appSecret;
    this.tokenCache = { token: null, expiresAt: 0 };
  }

  async getToken() {
    if (this.tokenCache.token && Date.now() < this.tokenCache.expiresAt) {
      return this.tokenCache.token;
    }

    const res = await fetch(`${LARK_BASE}/auth/v3/tenant_access_token/internal`, {
      method: 'POST',
      headers: { 'Content-Type': 'application/json' },
      body: JSON.stringify({
        app_id: this.appId,
        app_secret: this.appSecret
      })
    });

    const data = await res.json();
    this.tokenCache = {
      token: data.tenant_access_token,
      expiresAt: Date.now() + (data.expire - 300) * 1000
    };

    return this.tokenCache.token;
  }

  async request(method, path, body = null) {
    const token = await this.getToken();
    const options = {
      method,
      headers: {
        'Authorization': `Bearer ${token}`,
        'Content-Type': 'application/json'
      }
    };
    if (body) options.body = JSON.stringify(body);

    const res = await fetch(`${LARK_BASE}${path}`, options);
    const data = await res.json();

    if (data.code !== 0) {
      throw new Error(`Lark API error: ${data.msg} (code: ${data.code})`);
    }
    return data.data;
  }

  // Convenience methods
  async sendMessage(chatId, content, msgType = 'text') {
    return this.request('POST', '/im/v1/messages', {
      receive_id: chatId,
      msg_type: msgType,
      content: JSON.stringify(content)
    });
  }

  async getUserInfo(userId) {
    return this.request('GET', `/contact/v3/users/${userId}`);
  }

  async getCalendarEvents(calendarId, startTime, endTime) {
    return this.request('GET',
      `/calendar/v4/calendars/${calendarId}/events?start_time=${startTime}&end_time=${endTime}`
    );
  }

  async createDocument(folderId, title, content) {
    return this.request('POST', '/docx/v1/documents', {
      folder_token: folderId,
      title,
      document: { content }
    });
  }
}

module.exports = LarkAPIClient;

Using the Client in Skills

Each skill imports the shared client:

// /opt/clawdbot/skills/calendar-skill.js
const LarkAPIClient = require('../lib/lark-api');
const client = new LarkAPIClient(process.env.LARK_APP_ID, process.env.LARK_APP_SECRET);

async function handleCalendarQuery(context) {
  const today = new Date();
  const tomorrow = new Date(today);
  tomorrow.setDate(tomorrow.getDate() + 1);

  const events = await client.getCalendarEvents(
    context.user_calendar_id,
    today.toISOString(),
    tomorrow.toISOString()
  );

  if (events.items.length === 0) {
    return "You have no meetings scheduled for today. Enjoy the focus time!";
  }

  return events.items.map(e =>
    `${e.start_time} - ${e.end_time}: ${e.summary}`
  ).join('\n');
}

Webhook Event Handling

Lark sends events to your bot via webhooks. Configure the event subscription:

# /opt/clawdbot/config/lark-api.yaml
channel: lark
lark:
  app_id: "${LARK_APP_ID}"
  app_secret: "${LARK_APP_SECRET}"
  verification_token: "${LARK_VERIFY_TOKEN}"
  encrypt_key: "${LARK_ENCRYPT_KEY}"

event_subscriptions:
  - im.message.receive_v1      # New messages
  - im.message.reaction.created_v1  # Message reactions
  - calendar.event.changed_v1  # Calendar changes
  - approval.instance.status_changed  # Approval updates

Deploy on Lighthouse

Get your API development environment running:

  1. Visit the Tencent Cloud Lighthouse OpenClaw page to provision your instance.
  2. Select the "OpenClaw (Clawdbot)" application template under "AI Agents".
  3. Deploy by clicking "Buy Now" — the webhook endpoint and API client infrastructure are ready.

Error Handling Patterns

Lark APIs can fail in various ways. Handle each gracefully:

async function safeAPICall(fn, fallbackMessage) {
  try {
    return await fn();
  } catch (err) {
    if (err.message.includes('code: 99991663')) {
      // Token expired — will auto-refresh on next call
      return await fn();
    }
    if (err.message.includes('code: 230001')) {
      return "I don't have permission to access that resource. Please check the app's scopes.";
    }
    console.error('Lark API error:', err.message);
    return fallbackMessage || "Something went wrong with the Lark API. Please try again.";
  }
}

Testing API Integrations

Build a test script that validates all your API connections:

#!/bin/bash
# /opt/clawdbot/test-lark-api.sh
echo "=== Lark API Integration Test ==="

echo "1. Token fetch..."
TOKEN=$(curl -s -X POST "https://open.larksuite.com/open-apis/auth/v3/tenant_access_token/internal" \
  -H "Content-Type: application/json" \
  -d "{\"app_id\":\"$LARK_APP_ID\",\"app_secret\":\"$LARK_APP_SECRET\"}" | jq -r '.tenant_access_token')

[ -n "$TOKEN" ] && echo "   OK" || echo "   FAILED"

echo "2. Send test message..."
RESULT=$(curl -s -X POST "https://open.larksuite.com/open-apis/im/v1/messages" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"receive_id":"test_chat_id","msg_type":"text","content":"{\"text\":\"API test successful\"}"}')
echo "   $(echo $RESULT | jq -r '.msg')"

Wrapping Up

A well-built API layer is the backbone of every advanced Lark bot feature. Invest in a clean client architecture now, and every new skill you build will be easier.

  1. Visit https://www.tencentcloud.com/act/pro/intl-openclaw to deploy your API development environment.
  2. Select the "OpenClaw (Clawdbot)" template under "AI Agents".
  3. Deploy and start building Lark integrations that scale.

Good APIs make great bots.