lindy-observability

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Monitor Lindy AI agent health, task success rates, and credit consumption. Use when setting up monitoring, building dashboards, configuring alerts, or tracking agent performance over time. Trigger with phrases like "lindy monitoring", "lindy observability", "lindy metrics", "lindy logging", "lindy dashboard".

AI & Automation 2,266 stars 315 forks Updated today MIT

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# Lindy Observability ## Overview Monitor Lindy AI agent execution health, task completion rates, step-level failures, trigger frequency, and credit consumption. Lindy provides built-in task history in the dashboard. External observability requires webhook callbacks, the Task Completed trigger, and application-side metrics collection. ## Prerequisites - Lindy workspace with active agents - For external monitoring: webhook receiver + metrics stack (Prometheus/Grafana, Datadog) - For alerts: Slack or email integration configured ## Key Observability Signals | Signal | Source | Why It Matters | |--------|--------|---------------| | Task completion rate | Tasks tab / callback | Measures agent reliability | | Task duration | Task detail view | Tracks performance over time | | Step failure rate | Task detail (red steps) | Identifies broken actions | | Credit consumption | Billing dashboard | Budget tracking | | Trigger frequency | Task count over time | Detects trigger storms | | Agent error rate | Failed tasks / total tasks | Overall health indicator | ## Instructions ### Step 1: Dashboard Monitoring (Built-In) Lindy's Tasks tab provides per-agent monitoring: 1. Open agent > **Tasks** tab 2. Filter by status: **Completed**, **Failed**, **In Progress** 3. For failed tasks: click to see which step failed and why 4. Track patterns: same step failing? same time of day? same trigger type? ### Step 2: Task Completed Trigger (Agent-to-Agent Monitoring) Use Lindy's built-in **Task ...

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Author
jeremylongshore
Repository
jeremylongshore/claude-code-plugins-plus-skills
Created
7 months ago
Last Updated
today
Language
Python
License
MIT

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