trigger-dev
Trigger.dev expert for background jobs, AI workflows, and reliable async execution with excellent developer experience and TypeScript-first design.
What this skill does
# Trigger.dev Integration
Trigger.dev expert for background jobs, AI workflows, and reliable async
execution with excellent developer experience and TypeScript-first design.
## Principles
- Tasks are the building blocks - each task is independently retryable
- Runs are durable - state survives crashes and restarts
- Integrations are first-class - use built-in API wrappers for reliability
- Logs are your debugging lifeline - log liberally in tasks
- Concurrency protects your resources - always set limits
- Delays and schedules are built-in - no external cron needed
- AI-ready by design - long-running AI tasks just work
- Local development matches production - use the CLI
## Capabilities
- trigger-dev-tasks
- ai-background-jobs
- integration-tasks
- scheduled-triggers
- webhook-handlers
- long-running-tasks
- task-queues
- batch-processing
## Scope
- redis-queues -> bullmq-specialist
- pure-event-driven -> inngest
- workflow-orchestration -> temporal-craftsman
- infrastructure -> infra-architect
## Tooling
### Core
- trigger-dev-sdk
- trigger-cli
### Frameworks
- nextjs
- remix
- express
- hono
### Integrations
- openai
- anthropic
- resend
- stripe
- slack
- supabase
### Deployment
- trigger-cloud
- self-hosted
- docker
## Patterns
### Basic Task Setup
Setting up Trigger.dev in a Next.js project
**When to use**: Starting with Trigger.dev in any project
// trigger.config.ts
import { defineConfig } from '@trigger.dev/sdk/v3';
export default defineConfig({
project: 'my-project',
runtime: 'node',
logLevel: 'log',
retries: {
enabledInDev: true,
default: {
maxAttempts: 3,
minTimeoutInMs: 1000,
maxTimeoutInMs: 10000,
factor: 2,
},
},
});
// src/trigger/tasks.ts
import { task, logger } from '@trigger.dev/sdk/v3';
export const helloWorld = task({
id: 'hello-world',
run: async (payload: { name: string }) => {
logger.log('Processing hello world', { payload });
// Simulate work
await new Promise(resolve => setTimeout(resolve, 1000));
return { message: `Hello, ${payload.name}!` };
},
});
// Triggering from your app
import { helloWorld } from '@/trigger/tasks';
// Fire and forget
await helloWorld.trigger({ name: 'World' });
// Wait for result
const handle = await helloWorld.trigger({ name: 'World' });
const result = await handle.wait();
### AI Task with OpenAI Integration
Using built-in OpenAI integration with automatic retries
**When to use**: Building AI-powered background tasks
import { task, logger } from '@trigger.dev/sdk/v3';
import { openai } from '@trigger.dev/openai';
// Configure OpenAI with Trigger.dev
const openaiClient = openai.configure({
id: 'openai',
apiKey: process.env.OPENAI_API_KEY,
});
export const generateContent = task({
id: 'generate-content',
retry: {
maxAttempts: 3,
},
run: async (payload: { topic: string; style: string }) => {
logger.log('Generating content', { topic: payload.topic });
// Uses Trigger.dev's OpenAI integration - handles retries automatically
const completion = await openaiClient.chat.completions.create({
model: 'gpt-4-turbo-preview',
messages: [
{
role: 'system',
content: `You are a ${payload.style} writer.`,
},
{
role: 'user',
content: `Write about: ${payload.topic}`,
},
],
});
const content = completion.choices[0].message.content;
logger.log('Generated content', { length: content?.length });
return { content, tokens: completion.usage?.total_tokens };
},
});
### Scheduled Task with Cron
Tasks that run on a schedule
**When to use**: Periodic jobs like reports, cleanup, or syncs
import { schedules, task, logger } from '@trigger.dev/sdk/v3';
export const dailyCleanup = schedules.task({
id: 'daily-cleanup',
cron: '0 2 * * *', // 2 AM daily
run: async () => {
logger.log('Starting daily cleanup');
// Clean up old records
const deleted = await db.logs.deleteMany({
where: {
createdAt: { lt: new Date(Date.now() - 30 * 24 * 60 * 60 * 1000) },
},
});
logger.log('Cleanup complete', { deletedCount: deleted.count });
return { deleted: deleted.count };
},
});
// Weekly report
export const weeklyReport = schedules.task({
id: 'weekly-report',
cron: '0 9 * * 1', // Monday 9 AM
run: async () => {
const stats = await generateWeeklyStats();
await sendReportEmail(stats);
return stats;
},
});
### Batch Processing
Processing large datasets in batches
**When to use**: Need to process many items with rate limiting
import { task, logger, wait } from '@trigger.dev/sdk/v3';
export const processBatch = task({
id: 'process-batch',
queue: {
concurrencyLimit: 5, // Only 5 running at once
},
run: async (payload: { items: string[] }) => {
const results = [];
for (const item of payload.items) {
logger.log('Processing item', { item });
const result = await processItem(item);
results.push(result);
// Respect rate limits
await wait.for({ seconds: 1 });
}
return { processed: results.length, results };
},
});
// Trigger batch processing
export const startBatchJob = task({
id: 'start-batch',
run: async (payload: { datasetId: string }) => {
const items = await fetchDataset(payload.datasetId);
// Split into chunks of 100
const chunks = chunkArray(items, 100);
// Trigger parallel batch tasks
const handles = await Promise.all(
chunks.map(chunk => processBatch.trigger({ items: chunk }))
);
logger.log('Started batch processing', {
totalItems: items.length,
batches: chunks.length,
});
return { batches: handles.length };
},
});
### Webhook Handler
Processing webhooks reliably with deduplication
**When to use**: Handling webhooks from Stripe, GitHub, etc.
import { task, logger, idempotencyKeys } from '@trigger.dev/sdk/v3';
export const handleStripeEvent = task({
id: 'handle-stripe-event',
run: async (payload: {
eventId: string;
type: string;
data: any;
}) => {
// Idempotency based on Stripe event ID
const idempotencyKey = await idempotencyKeys.create(payload.eventId);
if (idempotencyKey.isNew === false) {
logger.log('Duplicate event, skipping', { eventId: payload.eventId });
return { skipped: true };
}
logger.log('Processing Stripe event', {
type: payload.type,
eventId: payload.eventId,
});
switch (payload.type) {
case 'checkout.session.completed':
await handleCheckoutComplete(payload.data);
break;
case 'customer.subscription.updated':
await handleSubscriptionUpdate(payload.data);
break;
}
return { processed: true, type: payload.type };
},
});
## Sharp Edges
### Task timeout kills execution without clear error
Severity: CRITICAL
Situation: Long-running AI task or batch process suddenly stops. No error in logs.
Task shows as failed in dashboard but no stack trace. Data partially processed.
Symptoms:
- Task fails with no error message
- Partial data processing
- Works locally, fails in production
- "Task timed out" in dashboard
Why this breaks:
Trigger.dev has execution timeouts (defaults vary by plan). When exceeded, the
task is killed mid-execution. If you're not logging progress, you won't know
where it stopped. This is especially common with AI tasks that can take minutes.
Recommended fix:
# Configure explicit timeouts:
```typescript
export const processDocument = task({
id: 'process-document',
machine: {
preset: 'large-2x', // More resources = longer allowed time
},
run: async (payload) => {
logger.log('Starting document processing', { docId: payload.id });
// Log progress at each step
logger.log('Step 1: Extracting text');
const text = await extractText(payload.fileUrl);
logger.log('Step 2: Generating embeddings', { textLength: text.length })Related in Design
contribute
IncludedLocal-only OSS contribution command center. Auto-refreshes the user's in-flight PR and issue state on invoke so conversations start with full context — no need to brief Claude on what's in flight. Helps the user find issues to contribute to on GitHub, builds per-repo dossiers of what each upstream expects (CLA, DCO, branch convention, AI policy, draft-first, review bots, issue templates), runs deterministic gates before any external action so AI-assisted contributions don't reach maintainers as slop. State is markdown-only: candidate files at ~/.contribute-system/candidates/, repo dossiers at ~/.contribute-system/research/, append-only event log at ~/.contribute-system/log.jsonl. No database, no cloud calls. Use when the user asks about their PRs / issues / contributions, wants to find new work to take on, claim an issue, build/refresh a repo's dossier, or draft a Design Issue or PR. Trigger with "/contribute", "what's my PR status", "find a contribution", "claim issue X", "draft a Design Issue for Y", "refresh dossier for Z".
architectural-analysis
IncludedUser-triggered deep architectural analysis of a codebase or scoped subtree across eight modes — information architecture, data flow, integration points, UI surfaces, interaction patterns, data model, control flow, and failure modes. This skill should be used when the user asks to "diagram this codebase," "map the architecture," "show the data flow," "give me an ERD," "trace control flow," "find the integration points," "verify the layout pattern," "audit the UX architecture," or any similar request whose primary deliverable is mermaid diagrams plus cited reports under docs/architecture/. Dispatches haiku/sonnet sub-agents in parallel for per-mode exploration, then verifies every citation mechanically before any node lands in a diagram. Not for one-off prose explanations of code (use code-explanation) or for high-level system design from scratch (use system-design).
mcp
IncludedModel Context Protocol (MCP) server development and tool management. Languages: Python, TypeScript. Capabilities: build MCP servers, integrate external APIs, discover/execute MCP tools, manage multi-server configs, design agent-centric tools. Actions: create, build, integrate, discover, execute, configure MCP servers/tools. Keywords: MCP, Model Context Protocol, MCP server, MCP tool, stdio transport, SSE transport, tool discovery, resource provider, prompt template, external API integration, Gemini CLI MCP, Claude MCP, agent tools, tool execution, server config. Use when: building MCP servers, integrating external APIs as MCP tools, discovering available MCP tools, executing MCP capabilities, configuring multi-server setups, designing tools for AI agents.
react-native-skia
IncludedDesign, build, debug, and optimise high-polish animated graphics in React Native or Expo using @shopify/react-native-skia, Reanimated, and Gesture Handler. Use when the user wants canvas-driven UI, shaders, paths, rich text, image filters, sprite fields, Skottie, video frames, snapshots, web CanvasKit setup, or performance tuning for custom motion-heavy elements such as loaders, hero art, cards, charts, progress indicators, particle systems, or gesture-driven surfaces. Also use when the user asks for fluid, glow, glass, blob, parallax, 60fps/120fps, or GPU-friendly animated effects in React Native, even if they do not explicitly say "Skia". Do not use for ordinary form/layout work with standard views.
plaid
IncludedProduct Led AI Development — guides founders from idea to launched product. Six capabilities: Idea (discover a product idea), Validate (pressure-test the idea against fatal flaws, problem reality, competition, and 2-week MVP feasibility), Plan (vision intake + document generation), Design (translate image references into a design.md spec), Launch (go-to-market strategy), and Build (roadmap execution). Use when someone says "PLAID", "plaid idea", "help me find an idea", "product idea", "idea from my business", "idea from my expertise", "plaid validate", "validate my idea", "pressure-test", "is this idea good", "find fatal flaws", "validate the problem", "plan a product", "define my vision", "generate a PRD", "product strategy", "plaid design", "design from image", "translate image to design", "create design.md", "extract design tokens", "plaid launch", "go-to-market", "launch plan", "GTM strategy", "launch playbook", "plaid build", "build the app", "start building", or "execute the roadmap".
nextjs-framer-motion-animations
IncludedAdds production-safe Motion for React or Framer Motion animations to Next.js apps, including reveal, hover and tap micro-interactions, whileInView, stagger, AnimatePresence, layout and layoutId transitions, reorder, scroll-linked UI, and lightweight route-content transitions. Use when the user asks to add, refactor, or debug Motion or Framer Motion in App Router or Pages Router codebases, especially around server/client boundaries, reduced motion, LazyMotion, bundle size, hydration, or route transitions. Avoid for GSAP-style timelines, WebGL or 3D scenes, heavy scroll storytelling, or CSS-only effects unless Motion is explicitly requested.