Monte Carlo Monitoring Advisor

Analyze data coverage and create monitoring checks for warehouse tables and AI agents; identify coverage gaps and generate monitors-as-code.

triggers:monitoring coveragecoverage gapscreate monitoradd a monitorunmonitored tables with anomaliesagent monitoringmonitor my agentmonitors-as-code

GitHub SKILL.md

What it does

This skill helps agents analyze data monitoring coverage across warehouses and use cases, find coverage gaps (including unmonitored tables with anomalies), and create table or agent monitors via preview-and-deploy flows. It consolidates guidance and reference procedures for data monitor creation, metric and validation monitors, and agent observability monitors.

When to use it

Use this skill when a user asks about monitoring coverage, wants to find which tables are unmonitored, needs to prioritize monitors by criticality or anomaly activity, or requests creation of monitors (table, metric, SQL, comparison, or agent evaluation monitors). Also use for agent observability tasks like tracing, latency monitoring, and agent evaluation monitors.

What's included

Scripts: none in this skill directory (has_references=true).
References: detailed creation and agent-monitor procedures in references/ alongside the skill (data-monitor-creation.md, agent-monitor-creation.md, per-type references).
Instructions: coverage workflow, importance-based fallback, SQL profiling guidance, and monitor creation preview-then-confirm patterns.

Compatible agents

Designed for coding/assistant agents that integrate with Monte Carlo MCP servers and MCP tooling (Claude Code, Cursor, Codex-style agent integrations).

Not yet audited

This skill has not been reviewed by our automated audit pipeline yet.

Information

Repository: mc-agent-toolkit
Stars: 86
Installs: 0

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