lindy-rate-limits

What this skill does

# Lindy Rate Limits & Credits

## Overview

Lindy uses a **credit-based** consumption model, not traditional API rate limits.
Every task (everything an agent does after being triggered) costs credits. Cost
scales with model intelligence, task complexity, premium actions, and duration.

## Credit Consumption Reference

| Factor | Credit Impact |
|--------|-------------|
| Basic model task | 1-3 credits |
| Large model task (GPT-4, Claude) | ~10 credits |
| Premium actions (webhooks, phone) | Additional credits |
| Phone calls (US/Canada landline) | ~20 credits/minute |
| Phone calls (international mobile) | 21-53 credits/minute |
| Minimum per task | 1 credit |

## Plan Credit Limits

| Plan | Credits/Month | Approx Tasks | Price |
|------|--------------|-------------|-------|
| Free | 400 | ~40-400 | $0 |
| Pro | 5,000 | ~500-1,500 | $49.99/mo |
| Business | 30,000 | ~3,000-30,000 | $299.99/mo |
| Enterprise | Custom | Custom | Custom |

**Important**: Credit limit enforcement is not instant. Lindy can only limit usage
*after* the limit has been breached, not precisely when it is reached. A task that
starts before the limit may complete and push usage slightly over.

## Instructions

### Step 1: Monitor Credit Usage

In the Lindy dashboard:

1. Navigate to **Settings > Billing**
2. Review current credit consumption
3. Track per-agent credit usage
4. Set up alerts for high-consumption agents

### Step 2: Reduce Per-Task Credit Cost

**Choose the right model for each step**:

| Task Type | Recommended Model | Credits |
|-----------|------------------|---------|
| Simple routing/classification | Gemini Flash | ~1 |
| Standard text generation | Claude Sonnet / GPT-4o-mini | ~3 |
| Complex reasoning/analysis | GPT-4 / Claude Opus | ~10 |
| Phone calls (simple) | Gemini Flash | ~20/min |
| Phone calls (complex) | Claude Sonnet | ~20/min |

**Reduce action count per task**:

- Combine multiple LLM calls into one prompt with structured output
- Use deterministic actions (Set Manually) instead of AI-powered fields where possible
- Eliminate unnecessary condition branches
- Use Run Code for data transformation instead of LLM steps

### Step 3: Optimize Trigger Frequency

Prevent credit waste from over-triggering:

```
Problem: Email Received trigger fires on ALL emails → 200 tasks/day
Solution: Add trigger filter: "sender contains '@customers.com'
          AND subject does not contain 'auto-reply'"
          → 20 tasks/day (90% reduction)
```

Trigger filter best practices:

- Use AND/OR conditions with condition groups
- Filter by sender, subject, label for email
- Filter by channel, keyword, user for Slack
- Add keyword filtering to exclude automated messages

### Step 4: Implement Webhook Rate Limiting

When your application triggers Lindy agents via webhooks, rate-limit on your side:

```typescript
// Rate limiter for outbound Lindy webhook triggers
class LindyRateLimiter {
  private tokens: number;
  private maxTokens: number;
  private refillRate: number; // tokens per second
  private lastRefill: number;

  constructor(maxPerMinute: number) {
    this.maxTokens = maxPerMinute;
    this.tokens = maxPerMinute;
    this.refillRate = maxPerMinute / 60;
    this.lastRefill = Date.now();
  }

  async acquire(): Promise<boolean> {
    const now = Date.now();
    const elapsed = (now - this.lastRefill) / 1000;
    this.tokens = Math.min(this.maxTokens, this.tokens + elapsed * this.refillRate);
    this.lastRefill = now;

    if (this.tokens >= 1) {
      this.tokens -= 1;
      return true;
    }
    return false;
  }

  get remaining(): number {
    return Math.floor(this.tokens);
  }
}

// Usage: limit to 30 webhook triggers per minute
const limiter = new LindyRateLimiter(30);

async function triggerLindy(payload: any) {
  if (!(await limiter.acquire())) {
    console.warn(`Rate limited. ${limiter.remaining} tokens remaining`);
    throw new Error('Lindy trigger rate limited');
  }
  await fetch(WEBHOOK_URL, {
    method: 'POST',
    headers: { 'Authorization': `Bearer ${SECRET}`, 'Content-Type': 'application/json' },
    body: JSON.stringify(payload),
  });
}
```

### Step 5: Budget Alerts

Set up monitoring to catch runaway agents before they drain credits:

```typescript
// Credit usage monitor
interface CreditAlert {
  threshold: number;   // percentage of monthly credits
  action: 'warn' | 'pause' | 'notify';
}

const alerts: CreditAlert[] = [
  { threshold: 50, action: 'warn' },    // 50% used: log warning
  { threshold: 80, action: 'notify' },  // 80% used: Slack alert
  { threshold: 95, action: 'pause' },   // 95% used: pause non-critical agents
];
```

### Step 6: Cost Attribution

Track which agents consume the most credits:

1. In dashboard: review per-agent task counts and credit usage
2. Identify top consumers — agents with frequent triggers or large models
3. For each high-cost agent, evaluate: Can the model be smaller? Can steps be consolidated?

## Resource Protection

Lindy includes built-in protection: when a task starts using more resources than
expected, Lindy **pauses and checks in** before continuing. This prevents runaway
agent steps from consuming unlimited credits.

## Error Handling

| Issue | Cause | Solution |
|-------|-------|----------|
| Credits exhausted mid-month | High-usage agents | Upgrade plan or optimize usage |
| Task paused by Lindy | Resource protection triggered | Review agent — likely looping |
| Webhook trigger returns 429 | Too many concurrent requests | Implement client-side rate limiting |
| Agent not running | Credit balance at zero | Wait for monthly reset or upgrade |

## Resources

- [Lindy Pricing](https://www.lindy.ai/pricing)
- [Lindy Documentation](https://docs.lindy.ai)

## Next Steps

Proceed to `lindy-security-basics` for API key and agent security.