Analyze a Monte Carlo monitor and recommend configuration changes to reduce alert noise. Supports metric, custom SQL, and validation monitors.
Generate SQL validation notebooks for dbt changes. Pass a GitHub PR URL or local dbt repo path.
Generates SQL validation notebooks for dbt PR changes with before/after comparison queries.
Triage Monte Carlo alerts interactively or build an automated workflow. Fetch, score, and troubleshoot alerts using MCP tools now, or design a reusable workflow that runs on a…
Automatically activates when a dbt model, SQL file, or table is referenced. Surfaces Monte Carlo context — table health, active alerts, lineage, blast radius — before any code is…
Guide users from coverage analysis to monitor creation. USE WHEN user asks what should I monitor, where are my gaps, improve coverage, or wants a systematic approach to monitoring…
Expert guide for pushing metadata, lineage, and query logs to Monte Carlo from any data warehouse.
Check the health of a data table/asset using Monte Carlo. Activates on "how is table X", "check health of X", "is X healthy", "status of X", "check on X table", or any…
Build a Connection Auth Rules for a Monte Carlo connection type. Fetches live connector schemas and transform steps from the apollo-agent repo.
Investigate data incidents and find root causes using Monte Carlo's observability data. Guides the agent through systematic investigation: alert lookup, lineage tracing, ETL…
Authors or extends a skill in mc-agent-toolkit. Gates for forbidden buckets and name collisions, applies CONTRIBUTING's extend-or-split rules, then edits a peer skill or hands off…
Analyze data coverage, create monitors for warehouse tables and AI agents. Covers coverage gaps, use-case analysis, data monitor creation, and agent observability.
Analyze a warehouse for stale, unused, or redundant tables via the analyze_storage_costs MCP tool. Classifies waste patterns and table categories, computes safety tiers, and…
Guides creation of Monte Carlo monitors via MCP tools, producing monitors-as-code YAML for CI/CD deployment.
Surfaces Monte Carlo data observability context (table health, alerts, lineage, blast radius) before SQL/dbt edits.