AGENT ATLASa field guide to agent workflows
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Automation & triggers

Monitoring & self-healing

An agent watches a system and acts when something drifts.

N agentsAdvanced

How it works

  1. 1Define what "healthy" looks like as explicit checks and thresholds.
  2. 2Poll or subscribe to the signal on a loop.
  3. 3On a breach, run a diagnosis and a bounded remediation — or alert a human.
  4. 4Log every detection and action; escalate if remediation fails twice.

Use it when

Keeping something within bounds over time — uptime, data quality, a metric — with automatic detection and a first-line response.

Reach for something else when

Issues need human judgment even to detect, or auto-remediation could make things worse without oversight.

Where you stay in the loop

The agent detects issues and runs first-line fixes; you decide which remediations are safe to automate versus which must page a human. The escalation rules are the moral core — when in doubt, it wakes you rather than guessing.

In the wild

An agent watches error rates; on a spike it checks recent deploys, posts a diagnosis, and pages a human if it can't resolve it.

Hand this to your agent

Design a monitoring agent as a runbook.

Help me define: (1) the signals to watch and their healthy thresholds, (2)
how often to check, (3) the diagnosis steps on a breach, (4) which
remediations are safe to auto-run vs must alert a human, (5) escalation
rules.

System to watch: <...>

Replace the <…> placeholders, paste it into your agent, and it'll scaffold the workflow with you.