monte-carlo-monitoring-advisor
Analyze data coverage, create monitors for warehouse tables and AI agents. Covers coverage gaps, use-case analysis, data monitor creation, and agent observability.
Profile →npx skills add sickn33/agentic-awesome-skills --skill monte-carlo-monitoring-advisor --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
This skill handles monitoring requests, including coverage analysis, data monitor creation, and AI agent monitoring, routing the user to the appropriate reference procedures based on intent.
How it works
- It delegates to specific Monte Carlo MCP-oriented workflows via a bundled plugin server, using tool names prefixed with mcp__plugin_mc-agent-toolkit_monte-carlo-mCP__ for access (e.g., get_alerts).
- It instructs the agent to access reference procedures located alongside the skill:
- references/data-monitor-creation.md
- references/agent-monitor-creation.md
- per-type references like references/data-.md and references/agent-.md
- When activated, it follows the Coverage workflow: discover warehouses, discover use cases, optionally perform SQL profiling if a database MCP server is present, then proceed to analysis and monitor previews for HIGH/MEDIUM priority tables.
- For coverage analysis, it may call tools such as get_use_case_table_summary, get_use_case_tables, get_monitors, get_asset_lineage, and various create_or_update_* monitor tools to generate preview YAMLs before live deployment.
- It emphasizes a two-call preview-then-confirm pattern for monitor creation, where dry_run=True returns a rendered YAML and dry_run=False deploys the monitor live.
- It includes steps to identify unmonitored tables with anomalies via get_unmonitored_tables_with_anomalies and to use get_table for details when narrowing candidates.
When to use it
Activate when the user asks about monitoring coverage, data coverage, coverage gaps, use cases, or agent observability, or asks to create or set up monitors for tables, fields, or AI agents. It is not used for merely querying data or responding to active alerts.
What it can touch
- Tools on the Monte Carlo MCP server accessed through the bundled plugin, including get_warehouses, get_use_cases, get_use_case_table_summary, get_use_case_tables, get_monitors, get_asset_lineage, get_audiences, get_unmonitored_tables_with_anomalies, search, get_table, get_queries_for_table, get_field_metric_definitions, get_domains, get_validation_predicates, and the five create_or_update_* monitor tools for tables, metrics, validations, SQL, and comparisons.
Caveats
- Prerequisites require a configured and authenticated Monte Carlo MCP server (monte-carlo-mcp).
- The risk level is stated as critical for this skill.
- The license is Apache-2.0.
# Monte Carlo Monitoring Advisor Skill This skill handles all monitoring requests -- coverage analysis, data monitor creation, and AI agent monitoring. It routes to the right reference file based on the user's intent. > **Monte Carlo tool routing (required):** Always call Monte Carlo MCP tools through this plugin's > bundled server, whose fully-qualified tool names are > `mcp__plugin_mc-agent-toolkit_monte-carlo-mcp__<tool>` (e.g. > `mcp__plugin_mc-agent-toolkit_monte-carlo-mcp__get_alerts`). Bare tool names used in this skill > (`get_alerts`, `search`, `get_table`, …) 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: - Data monitor creation procedure: `references/data-monitor-creation.md` (relative to this file) - Agent monitor creation procedure: `references/agent-monitor-creation.md` (relative to this file) - Per-type references: `references/data-*.md` and `references/agent-*.md` (relative to this file) ## When to activate this skill Activate
- When to activate this skill
- When NOT to activate this skill
- Prerequisites
- Available MCP tools
- Coverage and discovery tools
- Data monitor creation tools
- Agent monitoring tools
- Routing
- Coverage workflow
- Step 1: Discover warehouses
- Step 2: Discover use cases
- Step 3: Check for database MCP (optional)
- Use-case exploration
- Present use cases
What does the monte-carlo-monitoring-advisor skill do?
Analyze data coverage, create monitors for warehouse tables and AI agents. Covers coverage gaps, use-case analysis, data monitor creation, and agent observability.
How do I install it?
Run `npx skills add sickn33/agentic-awesome-skills --skill monte-carlo-monitoring-advisor --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From sickn33/agentic-awesome-skills, a repository with 44,414 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.