monte-carlo-prevent

name	monte-carlo-prevent
description	ALWAYS use this when the request matches Monte Carlo Prevent: Surfaces Monte Carlo data observability context (table health, alerts, lineage, blast radius) before SQL/dbt edits.

Monte Carlo Prevent Skill

Selective Reading Rule

Start with:

• references/usage-routing.md
• references/quality-checklist.md

Then load only the inherited docs, scripts, assets, or examples that match the user's actual task.

Selective Reading Rule

Start with:

• references/senior-master-standard.md

Then load only the references, scripts, assets, or examples needed for the user's actual task.

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, otherwise ask before editing.

Important: "Workflow 4 already ran this session" is NOT sufficient to proceed. Each distinct change prompt requires its own synthesis step connecting the MC findings to that specific change.

The synthesis must reference the specific columns, filters, or logic being changed in the current prompt — not just general table health.

Example:

• ✅ "Given 34 downstream models depend on is_paying_workspace, adding 'MC Internal' to the exclusion list will exclude these workspaces from all downstream health scores and exports. Confirm?"
• ❌ "Workflow 4 already ran. Making the edit now."

The only exception: if the user explicitly acknowledges the risk and confirms they want to skip (e.g. "I know the risks, just make the change") — proceed but note the skipped assessment.

Available MCP tools

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

Tool	Purpose
testConnection	Verify auth and connectivity
search	Find tables/assets by name
getTable	Schema, stats, metadata for a table
getAssetLineage	Upstream/downstream dependencies (call with mcons array + direction)
getAlerts	Active incidents and alerts
getMonitors	Monitor configs — filter by table using mcons array
getQueriesForTable	Recent query history
getQueryData	Full SQL for a specific query
createValidationMonitorMac	Generate validation monitors-as-code YAML
createMetricMonitorMac	Generate metric monitors-as-code YAML
createComparisonMonitorMac	Generate comparison monitors-as-code YAML
createCustomSqlMonitorMac	Generate custom SQL monitors-as-code YAML
getValidationPredicates	List available validation rule types
updateAlert	Update alert status/severity
setAlertOwner	Assign alert ownership
createOrUpdateAlertComment	Add comments to alerts
getAudiences	List notification audiences
getDomains	List MC domains
getUser	Current user info
getCurrentTime	ISO timestamp for API calls

Core workflows

Each workflow has detailed step-by-step instructions in references/workflows.md (Read tool).

1. Table health check

When: User opens a dbt model or mentions a table. What: Surfaces health, lineage, alerts, and risk signals. Auto-escalates to Workflow 4 if change intent is detected and risk signals are present.

2. Add a monitor

When: New column, filter, or business rule is added to a model. What: Suggests and generates monitors-as-code YAML using the appropriate create*MonitorMac tool. Saves to monitors/<table_name>.yml.

3. Alert triage

When: User is investigating an active data quality incident. What: Lists open alerts, checks table state, traces lineage for root cause, reviews recent queries.

4. Change impact assessment — REQUIRED before modifying a model

When: Any intent to modify a dbt model's logic, columns, joins, or filters. What: Surfaces blast radius, downstream dependencies, active incidents, monitor coverage, and query exposure. Produces a risk-tiered report with synthesis connecting findings to specific code recommendations. See references/workflows.md for the full assessment sequence, report format, and synthesis rules.

5. Change validation queries

When: Explicit engineer request only (e.g. "validate this change", "ready to commit"). What: Generates 3-5 targeted SQL queries to verify the change behaved as intended. Uses Workflow 4 context — requires both impact assessment and file edit in session.

---

Post-synthesis confirmation rules

Always end the synthesis with one clear, specific recommendation in plain English: "Given the above, I recommend: [specific action]"

If the risk is High or Medium: STOP and wait for confirmation before editing any file. You must ask the engineer and receive an explicit "yes", "go ahead", "proceed", or similar confirmation before making code changes. Say: "Do you want me to proceed with the edit?" Do NOT say: "Proceeding with the edit." — that skips the engineer's decision.

If the risk is Low: Use your judgment based on the synthesis findings. If the change is straightforward and the synthesis found no concerns, you may proceed. If anything is surprising or worth flagging, ask before editing.

---

Session markers

These markers coordinate between the skill and the plugin's hooks. Output each on its own line when the condition is met.

Impact check complete

After the engineer confirms (High/Medium) or after presenting the synthesis (Low), output one marker per assessed table. IMPORTANT: use only the table/model name, not the full MCON:

(Use the model filename without .sql extension — NOT "acme.analytics.orders" or "prod.public.client_hub")

How many markers to emit depends on how the assessment was triggered:

Hook-triggered (the pre-edit hook blocked an edit and instructed you to run the assessment): Be strict — only emit markers for tables whose lineage and monitor coverage were fetched directly via Monte Carlo tools in this session. If the engineer describes changes to multiple tables but only one was formally assessed, emit only one marker. The pre-edit hook will gate the other tables and prompt for their own Workflow 4 runs.

Voluntarily invoked (the engineer proactively asked for an impact assessment): Be looser — emit markers for all tables the assessment meaningfully covered, even if some were assessed via lineage context rather than direct MC tool calls. The engineer is already safety-conscious; don't force redundant assessments for tables they clearly considered.

Monitor coverage gap

When Workflow 4 finds zero custom monitors on a table's affected columns, output:

Use only the table/model name (NOT the full MCON). This allows the plugin's hooks to remind the engineer about monitor coverage at commit time. Only output this marker when the gap is specifically about the columns or logic being changed — not for general table-level monitor absence.

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.