monte-carlo-monitor-creation

name	monte-carlo-monitor-creation
description	Guides creation of Monte Carlo monitors via MCP tools, producing monitors-as-code YAML for CI/CD deployment.
category	AI & Agents
source	antigravity
tags	["mcp","claude","ai","agent","workflow","cro"]
url	https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/monte-carlo-monitor-creation

Monte Carlo Monitor Creation Skill

This skill teaches you to create Monte Carlo monitors correctly via MCP. Every creation tool runs in dry-run mode and returns monitors-as-code (MaC) YAML. No monitors are created directly -- the user applies the YAML via the Monte Carlo CLI or CI/CD.

Reference files live next to this skill file. Use the Read tool (not MCP resources) to access them:

• Metric monitor details: references/metric-monitor.md (relative to this file)
• Validation monitor details: references/validation-monitor.md (relative to this file)
• Custom SQL monitor details: references/custom-sql-monitor.md (relative to this file)
• Comparison monitor details: references/comparison-monitor.md (relative to this file)
• Table monitor details: references/table-monitor.md (relative to this file)

When to activate this skill

Activate when the user:

• Asks to create, add, or set up a monitor (e.g. "add a monitor for...", "create a freshness check on...", "set up validation for...")
• Mentions monitoring a specific table, field, or metric
• Wants to check data quality rules or enforce data contracts
• Asks about monitoring options for a table or dataset
• Requests monitors-as-code YAML generation
• Wants to add monitoring after new transformation logic (when the prevent skill is not active)

When NOT to activate this skill

Do not activate when the user is:

• Just querying data or exploring table contents
• Triaging or responding to active alerts (use the prevent skill's Workflow 3)
• Running impact assessments before code changes (use the prevent skill's Workflow 4)
• Asking about existing monitor configuration (use getMonitors directly)
• Editing or deleting existing monitors

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Available MCP tools

All tools are available via the monte-carlo MCP server.

Tool	Purpose
testConnection	Verify auth and connectivity before starting
search	Find tables/assets by name; use include_fields for columns
getTable	Schema, stats, metadata, domain membership, capabilities
getValidationPredicates	List available validation rule types for a warehouse
getDomains	List MC domains (only needed if table has no domain info)
createMetricMonitorMac	Generate metric monitor YAML (dry-run)
createValidationMonitorMac	Generate validation monitor YAML (dry-run)
createComparisonMonitorMac	Generate comparison monitor YAML (dry-run)
createCustomSqlMonitorMac	Generate custom SQL monitor YAML (dry-run)
createTableMonitorMac	Generate table monitor YAML (dry-run)

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Monitor types

Type	Tool	Use When
Metric	createMetricMonitorMac	Track statistical metrics on fields (null rates, unique counts, numeric stats) or row count changes over time. Requires a timestamp field for aggregation.
Validation	createValidationMonitorMac	Row-level data quality checks with conditions (e.g. "field X is never null", "status is in allowed set"). Alerts on INVALID data.
Custom SQL	createCustomSqlMonitorMac	Run arbitrary SQL returning a single number and alert on thresholds. Most flexible; use when other types don't fit.
Comparison	createComparisonMonitorMac	Compare metrics between two tables (e.g. dev vs prod, source vs target).
Table	createTableMonitorMac	Monitor groups of tables for freshness, schema changes, and volume. Uses asset selection at database/schema level.

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Procedure

Follow these steps in order. Do NOT skip steps.

Validation Phase (Steps 1-3) -- MUST complete before any creation tool is called

The number one error pattern is agents skipping validation and calling a creation tool with guessed or incomplete parameters. Every field in the creation call must be grounded in data retrieved during this phase. Do not proceed to Step 4 until Steps 1-3 are fully satisfied.

Step 1: Understand the request

Ask yourself:

• What does the user want to monitor? (a specific table, a metric, a data quality rule, cross-table consistency, freshness/volume at schema level)
• Which monitor type fits? Use the monitor types table