Agent skill · data analytics · sickn33
monte-carlo-performance-diagnosis
Diagnoses pipeline performance issues -- slow jobs, expensive queries, latency trends -- using Monte Carlo's cross-platform observability. Uses a tiered investigation approach: discover problems, bridge to affected tables, then drill into root causes.
Why this skill is useful
Adds a comprehensive set of diagnostic tools and workflows for analyzing data pipeline performance that the AI cannot generate on its own.
What it needs
Requires monte-carlo installed locally. Requires monte-carlo account access. About 5k tokens when loaded. Last updated 2026-08-07. 44,571 stars on the source repository.
What this skill does
Bundled upstream support Supporting files are included at skill-relative paths. See UPSTREAM-NOTICE.md for their pinned sources, licenses, hashes, and import changes. Monte Carlo Performance Diagnosis Skill This skill helps diagnose data pipeline performance issues using Monte Carlo's cross-platform observability data. It works across Airflow, dbt, Databricks, and warehouse query engines to find bottlenecks, detect regressions, and identify root causes. Monte Carlo tool routing (required): Always call Monte Carlo MCP tools through this plugin's bundled server, whose fully-qualified tool names are mcppluginmc-agent-toolkitmonte-carlo-mcp<tool> (e.g. mcppluginmc-agent-toolkitmonte-carlo-mcpgetalerts). Bare tool names used in this skill (getalerts, search, gettable, …) refer to that bundled server. If the session also has a separately-configured monte-carlo-mcp server, do not route to it — it may point at a different endpoint or credentials. Reference files live next to this skill file. Use the Read tool (not MCP resources) to access them: Tiered investigation approach: references/investigation-tiers.md (relative to this file) Query analysis patterns: references/query-analysis.md (relative to this file) When to activate this skill Activate when the user: Asks about slow pipelines, jobs, or queries Wants to find expensive or costly queries Mentions performance regressions or degradation Asks "why is this pipeline slow?" or "what's using the most compute?" Wants to compare performance over time or find bottleneck tasks Asks about failed or futile query patterns When NOT to activate this skill Do not activate when the user is: Investigating data quality issues (use the prevent skill) Looking at storage costs (use the storage-cost-analysis skill) Creating monitors (use the monitoring-advisor skill) Just querying data or exploring table contents Prerequisites The following MCP tools must be available (connect to Monte Carlo's MCP server): Discovery tools (Tier 1): getjobspe …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills sickn33/monte-carlo-performance-diagnosis--1d5ed0