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monte-carlo-prevent

Surfaces Monte Carlo data observability context (table health, alerts, lineage, blast radius) before SQL/dbt edits.

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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 (dbt_project.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.

Macros and snapshots — gate edits, skip auto-context

Macro files (macros/) and snapshot files (snapshots/) are not models, so do not auto-fetch Monte Carlo context (Workflow 1) when they are opened. However, macros are inlined into every model that calls them at compile time — a one-line macro change can silently alter dozens of models. Snapshots control historical tracking and are similarly sensitive.

The pre-edit hook gates these files. If the hook fires for a macro or snapshot, identify which models are affected and run the change impact assessment (Workflow 4) for those models before proceeding with the edit.


REQUIRED: Change impact assessment before any SQL edit

Before editing or writing any SQL for a dbt model or pipeline, you MUST run Workflow 4.

This applies whenever the user expresses intent to modify a model — including phrases like:

  • "I want to add a column…"
  • "Let me add / I'm adding…"
  • "I'd like to change / update / rename…"
  • "Can you add / modify / refactor…"
  • "Let's add…" / "Add a <column> column"
  • Any other description of a planned schema or logic change
  • "Exclude / filter out / remove [records/customers/rows]…"
  • "Adjust / increase / decrease [threshold/parameter/value]…"
  • "Fix / bugfix / patch [issue/bug]…"
  • "Revert / restore / undo [change/previous behavior]…"
  • "Disable / enable [feature/logic/flag]…"
  • "Clean up / remove [references/columns/code]…"
  • "Implement [backend/feature] for…"
  • "Create [models/dbt models] for…" (when modifying existing referenced tables)
  • "Increase / decrease / change [max_tokens/threshold/date constant/numeric parameter]…"
  • Any change to a hardcoded value, constant, or configuration parameter within SQL
  • "Drop / remove / delete [column/field/table]"
  • "Rename [column/field] to [new name]"
  • "Add [column]" (short imperative form, e.g. "add a created_at column")
  • Any single-verb imperative command targeting a column, table, or model (e.g. "drop X", "rename Y", "add Z", "remove W")

Parameter changes (threshold values, date constants, numeric limits) appear safe but silently change model output. Treat them the same as logic changes for impact assessment purposes.

Do not write or edit any SQL until the change impact assessment (Workflow 4) has been presented to the user. The assessment must come first — not after the edit, not in parallel.


Pre-edit gate — check before modifying any file

Before calling Edit, Write, or MultiEdit on any .sql or dbt model file, you MUST check:

  1. Has the synthesis step been run for THIS SPECIFIC CHANGE in the current prompt?
  2. If YES → proceed with the edit
  3. If NO → stop immediately, run Workflow 4, present the full report with synthesis connected to this specific change. If risk is High or Medium: ask "Do you want me to proceed with the edit?" and wait for explicit confirmation. If risk is Low: use judgment — proceed if straightforward and no concerns found, o