monte-carlo-incident-response

monte-carlo-incident-response is a skill for Claude Code from monte-carlo-data/mc-agent-toolkit. It costs 47 tokens per session (1,951 once invoked), scanned A, original, Apache-2.0.

A workflow for handling data incidents from initial investigation through root-cause analysis, repair, and prevention. A data incident is a problem such as stale, incorrect, or missing data.

In plain words
What is it for?
Responding to active alerts, broken or stale tables, pipeline failures, and other Monte Carlo data incidents.
Why use it?
It organizes the response to alerts and data failures into a complete sequence instead of leaving investigation and follow-up disconnected.

Skill for Claude Code

Written for Claude Code: when-to-use in frontmatter.

Good fit Responding to active alerts, broken or stale tables, pipeline failures, and other Monte Carlo data incidents.

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Install with agentmods
npx agentmods add skills/monte-carlo-data/mc-agent-toolkit/incident-response
Install

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.

Any agent
npx skills add monte-carlo-data/mc-agent-toolkit --skill incident-response
Clone the repo
git clone --depth 1 https://github.com/monte-carlo-data/mc-agent-toolkit

Made for: Claude Code.

Wrote 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.

agentmods badge for monte-carlo-incident-response

README.md
[![agentmods](https://agentmods.dev/badge/skills/monte-carlo-data/mc-agent-toolkit/incident-response.svg)](https://agentmods.dev/skills/monte-carlo-data/mc-agent-toolkit/incident-response)
Your own site
<a href="https://agentmods.dev/skills/monte-carlo-data/mc-agent-toolkit/incident-response"><img src="https://agentmods.dev/badge/skills/monte-carlo-data/mc-agent-toolkit/incident-response.svg" alt="Measured on agentmods" height="20"></a>
Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,951 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00047 $0.01951
Opus 5 $0.00023 $0.00975
Sonnet 5 $0.00009 $0.00390
Haiku 4.5 $0.00005 $0.00195

Measured 8d ago against content hash 21de933bbf82, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

monte-carlo-incident-response 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 8d 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.

skills/incident-response/SKILL.md · 147 lines

How it starts

The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Monte Carlo Incident Response Workflow

This workflow orchestrates the full lifecycle of a data incident by sequencing existing Monte Carlo skills. It does not contain investigation or remediation logic itself — each step loads the relevant skill's SKILL.md which has the actual instructions.

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.

When to activate this workflow

Activate when:

  • Context detection routes here (active alerts detected + incident intent)
  • User invokes /mc-incident-response
  • User asks to "respond to an incident", "handle this alert", "triage and fix"
  • User describes a data quality problem: "data is broken", "table is stale", "alert firing"

When NOT to activate this workflow

  • User wants to create monitors or check coverage without an active incident — use proactive monitoring workflow
  • User is editing a dbt model — defer to prevent skill (auto-activates via hooks)
  • User wants to check table health without an incident context — use asset-health directly
  • A skill is already active and handling the user's request

Workflow Steps

Step 1 (conditional): Triage — when user has multiple/unknown alerts
Step 2: Root Cause Analysis — the core investigation
Step 3: Remediation — fix or escalate
Step 4 (optional): Prevent Recurrence — add monitoring

Determine entry point

Before starting, determine which step to enter based on the user's context:

  • User has no specific alert ("I have alerts firing", "what's going on?") → Start at Step 1: Triage
  • User has a specific alert ID or table ("alert ABC-123", "stg_payments is stale") → Skip to Step 2: Root Cause Analysis
  • User knows the root cause ("the ETL job failed, help me fix it") → Skip to Step 3: Remediation
  • Alert is an agent-monitor alert (alert_types starting with "Agent ", or the user's issue is about an AI agent) → for the investigation, read ../troubleshoot-agent-traces/SKILL.md instead of ../analyze-root-cause/SKILL.md; the remediation and monitoring steps still apply
  • Ambiguous → Ask: "Do you have a specific alert or table you want to investigate, or should I check your recent alerts first?"

Read the full file on GitHub · 147 lines

Changes

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.

  1. 8d ago First seen · 147 lines · 47 tokens per session scan A 21de933bbf82

Subscribe to this mod's changes

monte-carlo-incident-response is a skill published in the GitHub repository monte-carlo-data/mc-agent-toolkit (91 stars, last pushed 14d ago), licensed Apache-2.0. It adds 47 tokens to every session and 1,951 once invoked, about $0.0002 per session on Opus 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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