monte-carlo-performance-diagnosis
OfficialDiagnose pipeline performance across platforms.
Authormonte-carlo-data
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Diagnoses data pipeline performance issues across Airflow, dbt, and Databricks by consolidating slow jobs, expensive queries, and latency regressions into a unified investigation workflow.
Core Features & Use Cases
- Tiered investigation approach (Tier 1 discovery, bridging to tables, Tier 2 diagnosis) to minimize unnecessary tool calls while delivering root-cause evidence.
- Cross-platform MCP toolset coverage including get_jobs_performance, get_top_slow_queries, get_tables_for_job, get_tasks_performance, get_change_timeline, get_query_rca, get_query_latency_distribution, and get_asset_lineage, plus get_warehouses for workspace context.
- Guidance on end-to-end troubleshooting with structured outputs and recommended remediation paths, enabling data teams to assess impact and explain changes to stakeholders.
Quick Start
Activate the skill to identify slow jobs and expensive queries across your pipelines and begin a Tier 1 discovery sequence.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: monte-carlo-performance-diagnosis Download link: https://github.com/monte-carlo-data/mc-agent-toolkit/archive/main.zip#monte-carlo-performance-diagnosis Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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