Agent skill · data analytics · sickn33
monte-carlo-prevent
Surfaces Monte Carlo data observability context (table health, alerts, lineage, blast radius) before SQL/dbt edits.
Why this skill is useful
Surfaces specific Monte Carlo data observability context and workflows that enhance data quality management in dbt models and SQL pipelines.
What it needs
About 7k tokens when loaded. Last updated 2026-08-07. 44,571 stars on the source repository.
What this skill does
Monte Carlo Prevent Skill This skill brings Monte Carlo's data observability context directly into your editor. When you're modifying a dbt model or SQL pipeline, use it to surface table health, lineage, active alerts, and to generate monitors-as-code without leaving Claude Code. Reference files live next to this skill file. Use the Read tool (not MCP resources) to access them: Full workflow step-by-step instructions: references/workflows.md (relative to this file) MCP parameter details: references/parameters.md (relative to this file) Troubleshooting: references/TROUBLESHOOTING.md (relative to this file) When to activate this skill Do not wait to be asked. Run the appropriate workflow automatically whenever the user: References or opens a .sql file or dbt model (files in models/) → run Workflow 1 Mentions a table name, dataset, or dbt model name in passing → run Workflow 1 Describes a planned change to a model (new column, join update, filter change, refactor) → STOP — run Workflow 4 before writing any code Adds a new column, metric, or output expression to an existing model → run Workflow 4 first, then ALWAYS offer Workflow 2 regardless of risk tier — do not skip the monitor offer Asks about data quality, freshness, row counts, or anomalies → run Workflow 1 Wants to triage or respond to a data quality alert → run Workflow 3 Present the results as context the engineer needs before proceeding — not as a response to a question. When NOT to activate this skill Do not invoke Monte Carlo tools for: Seed files (files in seeds/ directory) Analysis files (files in analyses/ directory) One-off or ad-hoc SQL scripts not part of a dbt project Configuration files (dbtproject.yml, profiles.yml, packages.yml) Test files unless the user is specifically asking about data quality If uncertain whether a file is a dbt model, check for {{ ref() }} or {{ source() }} Jinja references — if absent, do not activate. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills sickn33/monte-carlo-prevent--97f7c8