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Agent skill

Monte Carlo Monitor Creation

by sickn33 in sickn33/agentic-awesome-skills

Guides creation of Monte Carlo monitors via MCP tools, producing monitors-as-code YAML for CI/CD deployment.

MITAuto-check passedDevOps & Cloud

Install Monte Carlo Monitor Creation

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill monte-carlo-monitor-creation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills monte-carlo-monitor-creation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/monte-carlo-monitor-creation .claude/skills/monte-carlo-monitor-creation && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
monte-carlo-monitor-creation
GitHub stars
47k
Used in
1 other repo
Token cost
~2.9k tokens
SKILL.md length
1,429 words
Files
6 (incl. references)
Skills in repo
1,497
Repo updated
First seen
Licence
MIT

At a glance

Guides creation of Monte Carlo monitors via MCP tools, producing monitors-as-code YAML for CI/CD deployment.

  • Works in 8 steps: Understand the request → Identify the table(s) and columns → Handle domain assignment → …
  • Tasks that involve MCP servers
  • SKILL.md covers When to activate this skill, When NOT to activate this skill, Available MCP tools and Monitor types, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Monte Carlo Monitor Creation is an agent skill from sickn33/agentic-awesome-skills. Guides creation of Monte Carlo monitors via MCP tools, producing monitors-as-code YAML for CI/CD deployment.

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `references/comparison-monitor.md`, `references/custom-sql-monitor.md` and `references/metric-monitor.md`).

It sits in DevOps & Cloud, covering MCP servers and CI/CD. It works with Model Context Protocol. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.

When your agent uses it

  • Tasks that involve MCP servers
  • Tasks that involve CI/CD

Example prompts

  • “Use the monte-carlo-monitor-creation skill to guide creation of Monte Carlo monitors via MCP tools, producing monitors-as-code YAML for CI/CD…”
  • “/monte-carlo-monitor-creation”

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Understand the request
  2. Identify the table(s) and columns
  3. Handle domain assignment
  4. Load the sub-skill reference
  5. Ask about scheduling
  6. Confirm with the user
  7. Create the monitor
  8. Present results

What it can do on your machine

Read from SKILL.md and the folder at commit b84d35a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Monte Carlo Monitor Creation loads about 2.9k tokens when it runs, and up to ~19k if it reads all its reference files. Until then it costs about 34 tokens; SKILL.md has 1,429 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~34
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~19k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sickn33/agentic-awesome-skills at commit b84d35a, republished under its MIT licence (© sickn33). 1,429 words, ~2,914 tokens.

Download SKILL.mdSave it as .claude/skills/monte-carlo-monitor-creation/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
monte-carlo-monitor-creation
description
Guides creation of Monte Carlo monitors via MCP tools, producing monitors-as-code YAML for CI/CD deployment.
category
data
risk
safe
source
community
source_repo
monte-carlo-data/mc-agent-toolkit
source_type
community
date_added
2026-04-08
author
monte-carlo-data
tags
data-observability, monitoring, monte-carlo, monitors-as-code
tools
claude, cursor, codex

Monte Carlo Monitor Creation Skill

This skill teaches you to create Monte Carlo monitors correctly via MCP. Every creation tool runs in dry-run mode and returns monitors-as-code (MaC) YAML. No monitors are created directly -- the user applies the YAML via the Monte Carlo CLI or CI/CD.

Reference files live next to this skill file. Use the Read tool (not MCP resources) to access them:

  • Metric monitor details: references/metric-monitor.md (relative to this file)
  • Validation monitor details: references/validation-monitor.md (relative to this file)
  • Custom SQL monitor details: references/custom-sql-monitor.md (relative to this file)
  • Comparison monitor details: references/comparison-monitor.md (relative to this file)
  • Table monitor details: references/table-monitor.md (relative to this file)

When to activate this skill

Activate when the user:

  • Asks to create, add, or set up a monitor (e.g. "add a monitor for...", "create a freshness check on...", "set up validation for...")
  • Mentions monitoring a specific table, field, or metric
  • Wants to check data quality rules or enforce data contracts
  • Asks about monitoring options for a table or dataset
  • Requests monitors-as-code YAML generation
  • Wants to add monitoring after new transformation logic (when the prevent skill is not active)

When NOT to activate this skill

Do not activate when the user is:

  • Just querying data or exploring table contents
  • Triaging or responding to active alerts (use the prevent skill's Workflow 3)
  • Running impact assessments before code changes (use the prevent skill's Workflow 4)
  • Asking about existing monitor configuration (use getMonitors directly)
  • Editing or deleting existing monitors

Available MCP tools

All tools are available via the monte-carlo MCP server.

ToolPurpose
testConnectionVerify auth and connectivity before starting
searchFind tables/assets by name; use include_fields for columns
getTableSchema, stats, metadata, domain membership, capabilities
getValidationPredicatesList available validation rule types for a warehouse
getDomainsList MC domains (only needed if table has no domain info)
createMetricMonitorMacGenerate metric monitor YAML (dry-run)
createValidationMonitorMacGenerate validation monitor YAML (dry-run)
createComparisonMonitorMacGenerate comparison monitor YAML (dry-run)
createCustomSqlMonitorMacGenerate custom SQL monitor YAML (dry-run)
createTableMonitorMacGenerate table monitor YAML (dry-run)

Monitor types

TypeToolUse When
MetriccreateMetricMonitorMacTrack statistical metrics on fields (null rates, unique counts, numeric stats) or row count changes over time. Requires a timestamp field for aggregation.
ValidationcreateValidationMonitorMacRow-level data quality checks with conditions (e.g. "field X is never null", "status is in allowed set"). Alerts on INVALID data.
Custom SQLcreateCustomSqlMonitorMacRun arbitrary SQL returning a single number and alert on thresholds. Most flexible; use when other types don't fit.
ComparisoncreateComparisonMonitorMacCompare metrics between two tables (e.g. dev vs prod, source vs target).
TablecreateTableMonitorMacMonitor groups of tables for freshness, schema changes, and volume. Uses asset selection at database/schema level.

Procedure

Follow these steps in order. Do NOT skip steps.

Validation Phase (Steps 1-3) -- MUST complete before any creation tool is called

The number one error pattern is agents skipping validation and calling a creation tool with guessed or incomplete parameters. Every field in the creation call must be grounded in data retrieved during this phase. Do not proceed to Step 4 until Steps 1-3 are fully satisfied.

Step 1: Understand the request

Ask yourself:

  • What does the user want to monitor? (a specific table, a metric, a data quality rule, cross-table consistency, freshness/volume at schema level)
  • Which monitor type fits? Use the monitor types table above.
  • Does the user have all the details, or do they need guidance?

If the user's intent is unclear, ask a focused question before proceeding.

Step 2: Identify the table(s) and columns

If you don't have the table MCON:

  1. Use search with the table name and include_fields: ["field_names"] to find the MCON and get column names.
  2. If the user provided a full table ID like database:schema.table, search for it.
  3. Once you have the MCON, call getTable with include_fields: true and include_table_capabilities: true to verify capabilities and get domain info.

If you already have the MCON:

  1. Call getTable with the MCON, include_fields: true, and include_table_capabilities: true.

CRITICAL: You need the actual column names from getTable results. NEVER guess or hallucinate column names. This is the most common source of monitor creation failures.

For monitor types that require a timestamp column (metric monitors), review the column names and identify likely timestamp candidates. Present them to the user if ambiguous.

Step 3: Handle domain assignment

Monitors must be assigned to a domain that contains the table being monitored. The getTable response includes a domains list with uuid and name.

  1. If domains is empty: skip domain assignment.
  2. If domains has exactly one entry: default domain_id to that domain's UUID.
  3. If domains has multiple entries: present only those domains and ask the user to pick.

Do NOT present all account domains as options -- only domains that contain the table are valid.

ALWAYS check the table's domains BEFORE calling any creation tool.

Creation Phase (Steps 4-8)

Only enter this phase after the validation phase is complete with real data from MCP tools.

Step 4: Load the sub-skill reference

Based on the monitor type, read the detailed reference for parameter guidance:

  • Metric -- Read the detailed reference: references/metric-monitor.md (relative to this file)
  • Validation -- Read the detailed reference: references/validation-monitor.md (relative to this file)
  • Custom SQL -- Read the detailed reference: references/custom-sql-monitor.md (relative to this file)
  • Comparison -- Read the detailed reference: references/comparison-monitor.md (relative to this file)
  • Table -- Read the detailed reference: references/table-monitor.md (relative to this file)
Show full SKILL.md (544 more words)Show less
Step 5: Ask about scheduling

Skip this step for table monitors. Table monitors do not support the schedule field in MaC YAML — adding it will cause a validation error on montecarlo monitors apply. Table monitor scheduling is managed automatically by Monte Carlo.

For all other monitor types, the creation tools default to a fixed schedule running every 60 minutes. Present these options:

  1. Fixed interval -- any integer for interval_minutes (30, 60, 90, 120, 360, 720, 1440, etc.)
  2. Dynamic -- MC auto-determines when to run based on table update patterns.
  3. Loose -- runs once per day.

Schedule format in MaC YAML:

  • Fixed: schedule: { type: fixed, interval_minutes: <N> }
  • Dynamic: schedule: { type: dynamic }
  • Loose: schedule: { type: loose, start_time: "00:00" }
Step 6: Confirm with the user

Before calling the creation tool, present the monitor configuration in plain language:

  • Monitor type
  • Target table (and columns if applicable)
  • What it checks / what triggers an alert
  • Domain assignment
  • Schedule

Ask: "Does this look correct? I'll generate the monitor configuration."

NEVER call the creation tool without user confirmation.

Step 7: Create the monitor

Call the appropriate creation tool with the parameters built in previous steps. Always pass an MCON when possible. If only table name is available, also pass warehouse.

Step 8: Present results

CRITICAL: Always include the YAML in your response. The user needs copy-pasteable YAML.

  1. If a non-default schedule was chosen, modify the schedule section in the YAML before presenting.
  2. Wrap the YAML in the full MaC structure (see "MaC YAML format" section below).
  3. ALWAYS present the full YAML in a ```yaml code block.
  4. Explain where to put it and how to apply it (see below).
  5. ALWAYS use ISO 8601 format for datetime values.
  6. NEVER reformat YAML values returned by creation tools.

MaC YAML format

The YAML returned by creation tools is the monitor definition. It must be wrapped in the standard MaC structure to be applied:

yaml
montecarlo:
  <monitor_type>:
    - <returned yaml>

For example, a metric monitor would look like:

yaml
montecarlo:
  metric:
    - <yaml returned by createMetricMonitorMac>

Important: montecarlo.yml (without a directory path) is a separate Monte Carlo project configuration file -- it is NOT the same as a monitor definition file. Monitor definitions go in their own .yml files, typically in a monitors/ directory or alongside dbt model schema files.

Tell the user:

  • Save the YAML to a .yml file (e.g. monitors/<table_name>.yml or in their dbt schema)
  • Apply via the Monte Carlo CLI: montecarlo monitors apply --namespace <namespace>
  • Or integrate into CI/CD for automatic deployment on merge

Common mistakes to avoid

  • NEVER guess column names. Always get them from getTable.
  • NEVER skip the confirmation step (Step 6).
  • For metric monitors, aggregate_time_field MUST be a real timestamp column from the table.
  • For validation monitors, conditions match INVALID data, not valid data.
  • Always pass an MCON when possible. If only table name is available, also pass warehouse.
  • ALWAYS check table's domains BEFORE calling any creation tool.
  • ALWAYS use ISO 8601 format for datetime values.
  • NEVER reformat YAML values returned by creation tools.
  • Do not call creation tools before the validation phase is complete.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

© sickn33, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in skills/monte-carlo-monitor-creation of sickn33/agentic-awesome-skills.

  • SKILL.md
  • references/comparison-monitor.md
  • references/custom-sql-monitor.md
  • references/metric-monitor.md
  • references/table-monitor.md
  • references/validation-monitor.md

Open the folder on GitHubat commit b84d35a

Used in 1 other repository

We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Monte Carlo Monitor Creation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Monte Carlo Monitor Creation compared with similar skills
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Frontmcp Deploymentagentfront/frontmcp146—~9.2kAutomated safety check: NotesApache-2.0
Neon Postgres Branchesneondatabase/agent-skills100—~3.4kAutomated safety check: NotesApache-2.0
Engineering Advanced Skillsalirezarezvani/claude-skills28k—~1.1kAutomated safety check: PassMIT
Model Download Devopen-edge-platform/edge-ai-libraries171—~2.8kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about Monte Carlo Monitor Creation

What does Monte Carlo Monitor Creation do?

Guides creation of Monte Carlo monitors via MCP tools, producing monitors-as-code YAML for CI/CD deployment. Monte Carlo Monitor Creation is an agent skill from sickn33/agentic-awesome-skills. Guides creation of Monte Carlo monitors via MCP tools, producing monitors-as-code YAML for CI/CD deployment.

When should I use Monte Carlo Monitor Creation?

Monte Carlo Monitor Creation fits situations like: tasks that involve MCP servers; tasks that involve CI/CD.

How do I install Monte Carlo Monitor Creation in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill monte-carlo-monitor-creation -a claude-code`. Or copy the skill folder (skills/monte-carlo-monitor-creation in sickn33/agentic-awesome-skills) into .claude/skills/monte-carlo-monitor-creation in your project. Claude Code loads it when a task matches its description.

How do I install Monte Carlo Monitor Creation in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill monte-carlo-monitor-creation -a codex`. Or copy the skill folder (skills/monte-carlo-monitor-creation in sickn33/agentic-awesome-skills) into .agents/skills/monte-carlo-monitor-creation in your project. Codex loads it when a task matches its description.

Can I use Monte Carlo Monitor Creation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill monte-carlo-monitor-creation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/monte-carlo-monitor-creation, .gemini/skills/monte-carlo-monitor-creation, .github/skills/monte-carlo-monitor-creation and .opencode/skills/monte-carlo-monitor-creation in your project.

What does Monte Carlo Monitor Creation need to run?

SKILL.md names no scripts, command-line tools or credentials: Monte Carlo Monitor Creation is instructions for the agent only.

Does Monte Carlo Monitor Creation access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Monte Carlo Monitor Creation safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Monte Carlo Monitor Creation use?

Monte Carlo Monitor Creation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Monte Carlo Monitor Creation use?

About 2.9k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 16k tokens, read only when the agent opens those files.

What are the alternatives to Monte Carlo Monitor Creation?

Skills that share tags, products or a category with Monte Carlo Monitor Creation: Publishing (adeze/raindrop-mcp, 188 stars), Frontmcp Deployment (agentfront/frontmcp, 146 stars), Neon Postgres Branches (neondatabase/agent-skills, 100 stars) and Engineering Advanced Skills (alirezarezvani/claude-skills, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Monte Carlo Monitor Creation?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,405 GitHub stars. The repository holds 1,497 skills in this directory. The repository was last updated on October 9, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.