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 monitoring-advisorgit 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/monitoring-advisor)<a href="https://agentmods.dev/skills/monte-carlo-data/mc-agent-toolkit/monitoring-advisor"><img src="https://agentmods.dev/badge/skills/monte-carlo-data/mc-agent-toolkit/monitoring-advisor/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/monitoring-advisor"><img src="https://agentmods.dev/badge/skills/monte-carlo-data/mc-agent-toolkit/monitoring-advisor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 227 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 185 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00039 | $0.04731 |
| Opus 5.5 | $0.00016 | $0.01892 |
| Sonnet 5.5 | $0.00008 | $0.00946 |
| Haiku 4.5 | $0.00004 | $0.00473 |
Grade A, and why
monte-carlo-monitoring-advisor scanned grade A with 0 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 26d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 317 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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-configuredmonte-carlo-mcpserver, 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-*.mdandreferences/agent-*.md(relative to this file)
When to activate this skill
Activate when the user:
- Asks about monitoring coverage, data coverage, or coverage gaps
- Wants to understand what's monitored vs. not in their warehouse
- Asks about use cases, use-case criticality, or use-case analysis
- Wants to explore their data estate and find what needs monitoring
- Says things like "what should I monitor?", "where are my coverage gaps?", "show me my use cases"
- Asks about unmonitored tables with anomalies or importance-based prioritization
- 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)
- Asks about monitoring AI agents, agent latency, agent token usage, or agent quality
- Wants to set up alerts on agent behavior or execution patterns
- Says things like "monitor my agent", "track agent latency", "alert on agent errors", "set up performance monitoring for my agent", or asks for an agent latency SLO
- Asks about agent evaluation monitors, trajectory monitors, or validation monitors
- Mentions agent observability or agent monitoring
What ships with it
13 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- README.md 3.9 KB
- references/agent-evaluation-monitor.md 30 KB
- references/agent-metric-monitor.md 16 KB
- references/agent-monitor-creation.md 26 KB
- references/agent-span-fields.md 5.1 KB
- references/agent-trajectory-monitor.md 16 KB
- references/agent-validation-monitor.md 11 KB
- references/data-comparison-monitor.md 19 KB
- references/data-custom-sql-monitor.md 12 KB
- references/data-metric-monitor.md 18 KB
- references/data-monitor-creation.md 23 KB
- references/data-table-monitor.md 11 KB
- references/data-validation-monitor.md 19 KB
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.
- 26d ago Changed daa3e162ecc9
- 1mo ago Changed 0978148240e0
- 1mo ago First seen · 317 lines · 39 tokens per session scan A cb207ebc7689
monte-carlo-monitoring-advisor 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 39 tokens to every session and 4,731 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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