Core Lindy workflow for automating tasks and scheduling agents. Use when setting up automated workflows, scheduling agent runs, or creating trigger-based automations. Trigger with phrases like "lindy automation", "schedule lindy agent", "lindy workflow automation", "automate with lindy".
Installation
Details
Usage
After installing, this skill will be available to your AI coding assistant.
Verify installation:
skills listSkill Instructions
name: lindy-core-workflow-b description: | Core Lindy workflow for automating tasks and scheduling agents. Use when setting up automated workflows, scheduling agent runs, or creating trigger-based automations. Trigger with phrases like "lindy automation", "schedule lindy agent", "lindy workflow automation", "automate with lindy". allowed-tools: Read, Write, Edit version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io
Lindy Core Workflow B: Task Automation
Overview
Complete workflow for automating tasks and scheduling Lindy AI agents.
Prerequisites
- Completed
lindy-core-workflow-a(agent creation) - Agent ID ready for automation
- Clear automation requirements defined
Instructions
Step 1: Define Automation Spec
interface AutomationSpec {
agentId: string;
trigger: 'schedule' | 'webhook' | 'email' | 'event';
schedule?: string; // cron expression
webhookPath?: string;
emailTrigger?: string;
eventType?: string;
}
const automationSpec: AutomationSpec = {
agentId: 'agt_abc123',
trigger: 'schedule',
schedule: '0 9 * * *', // Daily at 9 AM
};
Step 2: Create Scheduled Automation
import { Lindy } from '@lindy-ai/sdk';
const lindy = new Lindy({ apiKey: process.env.LINDY_API_KEY });
async function createScheduledAutomation(spec: AutomationSpec) {
const automation = await lindy.automations.create({
agentId: spec.agentId,
type: 'schedule',
config: {
cron: spec.schedule,
timezone: 'America/New_York',
input: 'Run daily morning tasks',
},
});
console.log(`Created automation: ${automation.id}`);
return automation;
}
Step 3: Create Webhook Trigger
async function createWebhookAutomation(agentId: string, path: string) {
const automation = await lindy.automations.create({
agentId,
type: 'webhook',
config: {
path: path,
method: 'POST',
inputMapping: {
input: '{{body.message}}',
context: '{{body.context}}',
},
},
});
console.log(`Webhook URL: ${automation.webhookUrl}`);
return automation;
}
Step 4: Create Email Trigger
async function createEmailAutomation(agentId: string, triggerEmail: string) {
const automation = await lindy.automations.create({
agentId,
type: 'email',
config: {
triggerAddress: triggerEmail,
inputMapping: {
input: '{{email.body}}',
sender: '{{email.from}}',
subject: '{{email.subject}}',
},
},
});
console.log(`Forward emails to: ${automation.triggerEmail}`);
return automation;
}
Output
- Configured automation triggers
- Scheduled or event-based agent runs
- Webhook endpoints for external triggers
- Email triggers for inbox automation
Error Handling
| Error | Cause | Solution |
|---|---|---|
| Invalid cron | Bad schedule format | Use standard cron syntax |
| Webhook conflict | Path already used | Choose unique webhook path |
| Agent not found | Invalid agent ID | Verify agent exists |
Examples
Multi-Trigger Setup
async function setupAutomations(agentId: string) {
// Daily summary at 9 AM
await lindy.automations.create({
agentId,
type: 'schedule',
config: { cron: '0 9 * * *', input: 'Generate daily summary' },
});
// Webhook for external events
await lindy.automations.create({
agentId,
type: 'webhook',
config: { path: '/events', method: 'POST' },
});
// Email trigger for support
await lindy.automations.create({
agentId,
type: 'email',
config: { triggerAddress: 'support@mycompany.com' },
});
}
Resources
Next Steps
Proceed to lindy-common-errors for troubleshooting guidance.
More by jeremylongshore
View allOauth Callback Handler - Auto-activating skill for API Integration. Triggers on: oauth callback handler, oauth callback handler Part of the API Integration skill category.
Rabbitmq Queue Setup - Auto-activating skill for Backend Development. Triggers on: rabbitmq queue setup, rabbitmq queue setup Part of the Backend Development skill category.
evaluating-machine-learning-models: This skill allows Claude to evaluate machine learning models using a comprehensive suite of metrics. It should be used when the user requests model performance analysis, validation, or testing. Claude can use this skill to assess model accuracy, precision, recall, F1-score, and other relevant metrics. Trigger this skill when the user mentions "evaluate model", "model performance", "testing metrics", "validation results", or requests a comprehensive "model evaluation".
building-neural-networks: This skill allows Claude to construct and configure neural network architectures using the neural-network-builder plugin. It should be used when the user requests the creation of a new neural network, modification of an existing one, or assistance with defining the layers, parameters, and training process. The skill is triggered by requests involving terms like "build a neural network," "define network architecture," "configure layers," or specific mentions of neural network types (e.g., "CNN," "RNN," "transformer").
