monte-carlo-proactive-monitoring

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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 across their data estate.

AI & Automation 90 stars 7 forks Updated yesterday Apache-2.0

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Quality Score: 91/100

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Issue Health 10%
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Description 5%
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Skill Content

# Monte Carlo Proactive Monitoring Workflow This workflow guides users through improving their monitoring coverage by sequencing existing Monte Carlo skills. It does not contain coverage analysis or monitor creation logic itself — each step loads the relevant skill's SKILL.md which has the actual instructions. ## When to activate this workflow Activate when: - Context detection routes here (coverage intent + data project detected) - User invokes `/mc-proactive-monitoring` - User asks "what should I monitor?", "where are my gaps?", "improve coverage" - User wants a systematic approach to monitoring — not just creating one specific monitor ## When NOT to activate this workflow - User already knows exactly what monitor to create (e.g., "create a freshness monitor on X") — route to `monitoring-advisor` directly - User is responding to an active incident — use incident response workflow - User is editing a dbt model — defer to `prevent` skill (auto-activates via hooks) - A skill is already active and handling the user's request --- ## Workflow Steps ``` Step 1 (conditional): Assess current state — when user has specific tables in mind Step 2: Identify gaps — the core of this workflow Step 3: Create monitors — act on identified gaps ``` ### Determine entry point Before starting, determine which step to enter based on the user's context: - **User mentions specific tables** ("what monitoring do I have on stg_payments?", "check my orders tables") → Start at **Step 1: Asses...

Details

Author
monte-carlo-data
Repository
monte-carlo-data/mc-agent-toolkit
Created
5 months ago
Last Updated
yesterday
Language
Python
License
Apache-2.0

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