Official Monte Carlo toolkit for AI coding agents. Skills and plugins that bring data and agent observability — monitoring, triaging, troubleshooting, health checks — into Claude Code, Cursor, and more.
Authors or extends a skill in mc-agent-toolkit. Gates for forbidden buckets and name collisions, applies CONTRIBUTING's extend-or-split rules, then edits a peer skill or hands off to Anthropic's skill-creator and walks the registration checklist.
Investigate data incidents and find root causes using Monte Carlo's observability data. Guides the agent through systematic investigation: alert lookup, lineage tracing, ETL checks, query analysis, and data profiling. Activates when a user asks about data issues, incidents, alerts, or why data looks wrong.
Check the health of a data table/asset using Monte Carlo. Activates on "how is table X", "check health of X", "is X healthy", "status of X", "check on X table", or any health/status question about a data asset.
Triage Monte Carlo alerts interactively or build an automated workflow. Fetch, score, and troubleshoot alerts using MCP tools now, or design a reusable workflow that runs on a schedule.
Route data-related requests to the right Monte Carlo skill or workflow. USE WHEN alerts, incidents, data broken, stale, coverage gaps, data quality, or any ambiguous data observability request.
Orchestrate incident response — triage, root cause, remediate, prevent recurrence. USE WHEN active alerts, data broken, stale, pipeline failure, or investigate and fix a data incident.
Instrument a new AI agent in a Python codebase for Monte Carlo Agent Observability. Detects AI libraries, installs the Monte Carlo OpenTelemetry SDK, and proposes tracing setup and decorator placements as diffs. Asks before editing any file.
Analyze data coverage, create monitors for warehouse tables and AI agents. Covers coverage gaps, use-case analysis, data monitor creation, and agent observability.
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. Activates when a user asks about slow pipelines, expensive queries…
Shift-left safety net for dbt/SQL model edits. Runs change impact assessment before edits, generates SQL validation queries after, and executes them via /mc-validate run. Delegates health and monitor creation to peer skills.
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.
Expert guide for Monte Carlo's push ingestion model. Use this skill whenever a customer or engineer mentions: pushing data to Monte Carlo, the IngestionService, pycarlo push APIs, build me a collection script, push metadata/lineage/query logs, invocationid tracing, custom lineage nodes or edges, deleting push tables…
Reinforces an AI agent by turning Monte Carlo's reinforcement loop diagnosis into code fixes. Reads the daily reinforcement loop report for an agent's workflows, ranks the diagnosed issues, proposes what to fix, and — with the user's approval at each step — opens a pull request. Activates on "fix my agent", "improve…
Investigate and remediate data quality alerts using Monte Carlo MCP tools. Runs root cause analysis, assesses blast radius, discovers available tools (MCP/CLI/API), proposes and executes fixes, or escalates with full context when uncertain.
Analyze a warehouse for stale, unused, or redundant tables via the analyzestoragecosts MCP tool. Classifies waste patterns and table categories, computes safety tiers, and handles category drill-downs and lineage follow-ups.
Troubleshoots Monte Carlo AI agent alerts and traces — eval score drops, latency/token spikes, trajectory and validation breaches. Not for data incidents (monte-carlo-analyze-root-cause) or monitor creation (monte-carlo-monitoring-advisor).
Analyze a Monte Carlo monitor and recommend config changes to reduce alert noise. Supports metric, custom SQL, validation, table, and agent (metric, evaluation, trajectory, validation) monitors. Fetches the report, identifies patterns, and suggests tuning.
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: