Monte Carlo Prevent Skill

Overview

This public intake copy packages

plugins/antigravity-awesome-skills-claude/skills/monte-carlo-prevent

https://github.com/sickn33/antigravity-awesome-skills

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses

metadata.json

ORIGIN.md

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)

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: REQUIRED: Change impact assessment before any SQL edit, Pre-edit gate — check before modifying any file, Available MCP tools, Session markers, Limitations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• 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
• 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

Operating Table

metadata.json

ORIGIN.md

references/TROUBLESHOOTING.md

references/parameters.md

## Related Skills

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Each workflow has detailed step-by-step instructions in references/workflows.md (Read tool).
2. Table health check When: User opens a dbt model or mentions a table.
3. What: Surfaces health, lineage, alerts, and risk signals.
4. Auto-escalates to Workflow 4 if change intent is detected and risk signals are present.
5. Add a monitor When: New column, filter, or business rule is added to a model.
6. What: Suggests and generates monitors-as-code YAML using the appropriate create*MonitorMac tool.
7. Saves to monitors/<table_name>.yml.

Imported Workflow Notes

Imported: Core workflows

Each workflow has detailed step-by-step instructions in

references/workflows.md

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

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

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.

Imported: 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.

Examples

Example 1: Ask for the upstream workflow directly

Use @monte-carlo-prevent to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @monte-carlo-prevent against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @monte-carlo-prevent for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @monte-carlo-prevent using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• 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.
• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.

Imported Operating Notes

Imported: 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.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in

plugins/antigravity-awesome-skills-claude/skills/monte-carlo-prevent

metadata.json

ORIGIN.md

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated

SKILL.md

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @monte-carlo-monitor-creation

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @monte-carlo-push-ingestion

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @monte-carlo-validation-notebook

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @moodle-external-api-development

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

references

references/TROUBLESHOOTING.md

examples

examples/n/a

scripts

scripts/n/a

agents

agents/n/a

assets

assets/n/a

• TROUBLESHOOTING.md
• parameters.md
• workflows.md
• TROUBLESHOOTING.md
• parameters.md
• workflows.md

Imported Reference Notes

Imported: Pre-edit gate — check before modifying any file

Before calling Edit, Write, or MultiEdit on any

.sql

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.

Imported: Available MCP tools

All tools are available via the

monte-carlo

testConnection

search

getTable

getAssetLineage

getAlerts

getMonitors

getQueriesForTable

getQueryData

createValidationMonitorMac

createMetricMonitorMac

createComparisonMonitorMac

createCustomSqlMonitorMac

getValidationPredicates

updateAlert

setAlertOwner

createOrUpdateAlertComment

getAudiences

getDomains

getUser

getCurrentTime

Imported: 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.

Imported: 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.