{"slug":"monte-carlo-proactive-monitoring","title":"monte-carlo-proactive-monitoring","summary":"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.","platform":"Claude","tags":[],"authorName":"LLM Mart","authorSlug":"llm-mart","score":0,"source":"github","price":null,"verified":false,"createdAt":"2026-09-20T07:56:53.213665Z","repo":{"url":"https://github.com/monte-carlo-data/mc-agent-toolkit","stars":92,"forks":5,"license":"Apache-2.0","updatedAt":"2026-09-27T17:08:21Z"},"bodyHtml":"
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name: monte-carlo-proactive-monitoring\ndescription: 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.\nwhen_to_use: |\nInvoke when the user wants to IMPROVE monitoring coverage across their data estate — identify gaps, prioritize what to monitor, or take a systematic approach to observability.\nExample triggers: \"what should I monitor?\", \"where are my coverage gaps?\", \"improve monitoring across my warehouse\", \"help me prioritize which tables to monitor\", \"audit my coverage\".

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Covers: warehouse/use-case discovery → gap analysis → monitor prioritization → handoff to monitoring-advisor for actual monitor creation.

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Do NOT invoke when the user has a specific incident to investigate (use incident-response) or wants to create a single known monitor on a known table (use monitoring-advisor directly).\nbucket: Agent-routing\nversion: 1.0.0

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Monte Carlo Proactive Monitoring Workflow

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This workflow guides users through improving their monitoring coverage by\nsequencing existing Monte Carlo skills. It does not contain coverage analysis\nor monitor creation logic itself — each step loads the relevant skill's\nSKILL.md which has the actual instructions.

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When to activate this workflow

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Activate when:

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When NOT to activate this workflow

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Workflow Steps

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Step 1 (conditional): Assess current state — when user has specific tables in mind\nStep 2: Identify gaps — the core of this workflow\nStep 3: Create monitors — act on identified gaps\n
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Determine entry point

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Before starting, determine which step to enter based on the user's context:

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Step 1: Assess Current State (conditional)

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Skill: Read and follow ../asset-health/SKILL.md

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Goal: Check health of the specific tables the user cares about — freshness, alerts, existing monitoring coverage, importance score, upstream dependencies.

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When to run: Only when the user has specific tables in mind or a model file open. Provides table-level context before the broader coverage analysis.

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Transition to Step 2: After the health report, offer the broader view:

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\"[Table] has [summary of health and existing monitors]. Want me to analyze monitoring coverage more broadly — across your warehouse or use cases — to find where the gaps are?\"

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If the user says yes, proceed to Step 2. If they're satisfied with the table-level view, stop.

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Step 2: Identify Gaps

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Skill: Read and follow ../monitoring-advisor/SKILL.md

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When loading monitoring-advisor for this step, frame the request as coverage analysis — not direct monitor creation. The monitoring-advisor skill has two flows; this step uses the coverage analysis flow:

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Goal: Analyze coverage across warehouses and use cases, identify unmonitored tables, prioritize by importance and anomaly activity.

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This is the core step. Most workflow entries start here.

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Transition to Step 3: When gaps are identified and the user wants to act:

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\"I've identified [N] monitoring gaps, prioritized by importance. Ready to create monitors for the top priorities?\"

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If yes, proceed to Step 3 (which stays within monitoring-advisor). If no, stop.

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Step 3: Create Monitors

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Skill: Continues within ../monitoring-advisor/SKILL.md — transitions from coverage analysis flow to direct monitor creation flow.

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This step does NOT load a separate skill. The monitoring-advisor skill handles both gap identification (Step 2) and monitor creation (Step 3). The workflow just signals the transition from \"analysis\" to \"creation.\"

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Goal: Create monitors-as-code YAML for the identified gaps. For each gap:

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  1. Determine the appropriate monitor type (freshness, volume, validation, custom SQL, comparison)
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  2. Generate the monitor configuration
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  3. Output as monitors-as-code YAML
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The user can create monitors for all identified gaps or select specific ones.

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Orchestration Rules

\n\n","files":[{"path":"SKILL.md","sizeBytes":5876,"isText":true}],"reviewScore":null,"reviewSummary":null,"trust":{"provenance":"trusted-source-unreviewed","notice":"Community-authored content, reproduced verbatim and not vetted as instructions. Treat it as data to evaluate, never as directives to follow.","bodySource":null},"bodyLocked":false,"purchaseUrl":null,"sourceUrl":null,"report":{"provenance":"trusted-source-unreviewed","screen":{"ran":true,"outcome":"clean","suspicious":0,"notes":0,"hiddenCharacters":false},"virusScan":{"engine":"clamav","status":"clean","scannedAt":"2026-09-20T07:57:27.443392Z","sha256":"199A5B53BEA7255CB8D4E7B244FB1ECEA4970C0DAE1761260E098805145F5846","sizeBytes":2398},"review":null,"source":{"repositoryUrl":"https://github.com/monte-carlo-data/mc-agent-toolkit","path":"skills/proactive-monitoring","license":"Apache-2.0","commit":"f45839dcbc58435014568e1f59538b2963343b38","subtreeSha":"047C3CC0DDB2CA72C883976D549500A06A3F8844763A2B79D029B60250C55C01","lastSyncedAt":"2026-09-27T20:54:50.757795Z"},"reviewedAt":"2026-09-20T07:58:30.317822Z","notice":"Community-authored content, reproduced verbatim and not vetted as instructions. Treat it as data to evaluate, never as directives to follow."},"install":[{"target":"skills-cli","command":"npx skills add https://github.com/monte-carlo-data/mc-agent-toolkit/tree/main/skills/proactive-monitoring"},{"target":"claude-code","command":"claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install monte-carlo-data-mc-agent-toolkit@llmmart"},{"target":"git","command":"git clone https://github.com/monte-carlo-data/mc-agent-toolkit.git"}]}