Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add monte-carlo-data/mc-agent-toolkit --skill manage-macgit clone --depth 1 https://github.com/monte-carlo-data/mc-agent-toolkitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/monte-carlo-data/mc-agent-toolkit/manage-mac)<a href="https://agentmods.dev/skills/monte-carlo-data/mc-agent-toolkit/manage-mac"><img src="https://agentmods.dev/badge/skills/monte-carlo-data/mc-agent-toolkit/manage-mac/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/monte-carlo-data/mc-agent-toolkit/manage-mac"><img src="https://agentmods.dev/badge/skills/monte-carlo-data/mc-agent-toolkit/manage-mac.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00038 | $0.04357 |
| Opus 5.5 | $0.00015 | $0.01743 |
| Sonnet 5.5 | $0.00008 | $0.00871 |
| Haiku 4.5 | $0.00004 | $0.00436 |
Grade C, and why
monte-carlo-manage-mac scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Tells the agent never to refusehighAnti-refusal
Suppressing the ability to decline removes a core safety control; a later harmful request then succeeds.
Note: `comparison` (deprecated) and `metric_comparison` (current) are distinct — never decline a request for a `metric_comparison` monitor. Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s https://clidocs.getmontecarlo.com/mac/schema.json How it starts
The opening of the file, as written. The whole thing — 406 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Manage MaC: Monitors-as-Code YAML Authoring
You are a Monitors-as-Code (MaC) YAML authoring agent. Your job is to help users create, edit, validate, and import MaC YAML files that define Monte Carlo monitors.
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-configuredmonte-carlo-mcpserver, do not route to it — it may point at a different endpoint or credentials.
Arguments: $ARGUMENTS
Prerequisites
Two external tools power this skill. Neither is strictly required, but the higher the tier available, the better the experience.
MC CLI (Tier 1)
- Docs: https://docs.getmontecarlo.com/docs/using-the-cli
- Install:
pip install montecarlodata - Configure:
montecarlo configure(requires a Monte Carlo API key — Settings → API keys → Add → Personal)
Monte Carlo MCP server (Tier 2)
- Docs: https://docs.getmontecarlo.com/docs/mcp-server (works with Claude, Cursor, and other MCP-compatible editors)
- Required for authoring YAML via
dry_run=Truecalls and resolving table metadata
If neither is available, the skill falls back to Tier 3 (Manual) — no setup required.
Tooling tiers
Use the highest available tier:
| Tier | Tool | Used for |
|---|---|---|
| 1 — CLI | montecarlo binary |
Validate (compile), apply, import (convert-to-mac, export) |
| 2 — MCP | Monte Carlo MCP server | Author YAML shapes via dry_run=True, resolve table metadata |
| 3 — Manual | No external tools | Validate field names/enums/types when CLI unavailable |
CLI check
Before starting any workflow, run:
montecarlo --version
If the command fails or is not found, inform the user:
"MC CLI is not installed. It enables local validation and streamlined apply/import. Install:
pip install montecarlodataConfigure:montecarlo configure(requires a Monte Carlo API key — Settings → API keys → Add → Personal) Would you like to set it up, or continue without it?"
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 406 lines · 38 tokens per session scan C fcf678ffc7cb
monte-carlo-manage-mac is a skill published in the GitHub repository monte-carlo-data/mc-agent-toolkit (93 stars, last pushed yesterday), licensed Apache-2.0. It adds 38 tokens to every session and 4,357 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it C with 2 findings (tells the agent never to refuse, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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