micsapp Lindy AI Observability
Overview
Monitor Lindy AI agent execution health, automation success rates, and response latency. Key observability signals for Lindy include agent run duration, step-level success/failure within multi-step automations, trigger frequency (how often agents are invoked), and per-agent cost tracking based on Lindy's per-agent pricing model where each active agent incurs a fixed monthly cost.
Prerequisites
- Lindy Team or Enterprise workspace
- API access with a valid
LINDY_API_KEY - External monitoring stack (Prometheus/Grafana, Datadog, or similar)
Instructions
Step 1: Poll Agent Run Status via API
Step 2: Emit Metrics from Run Data
Step 3: Set Up Webhook-Based Real-Time Monitoring
Configure Lindy webhooks to push events on agent run completion:
Step 4: Alert on Agent Failures
Step 5: Build a Dashboard
Key panels: agent run success/failure rate (stacked bar), run duration p50/p95 by agent, step failure heatmap (which steps fail most), trigger frequency (runs/hour), and active agent count vs billing (since Lindy charges per active agent).
For detailed implementation code and configurations, load the reference guide:
Read(${CLAUDE_SKILL_DIR}/references/implementation-guide.md)
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| Webhook not delivering | Endpoint returning non-2xx | Fix endpoint, check Lindy webhook logs |
| Run duration spike | Downstream API slow in agent step | Check step-level timing in run details |
| Agent marked inactive | No triggers firing | Verify trigger configuration (schedule, webhook, email) |
| Metrics exporter missing data | API rate limit on /runs |
Reduce polling frequency, use webhooks instead |
Examples
Basic usage: Apply lindy observability to a standard project setup with default configuration options.
Advanced scenario: Customize lindy observability for production environments with multiple constraints and team-specific requirements.
Output
- Configuration files or code changes applied to the project
- Validation report confirming correct implementation
- Summary of changes made and their rationale
See monitoring implementation details for output format specifications.
Resources
- Official monitoring documentation
- Community best practices and patterns
- Related skills in this plugin pack