| name | automated-triage |
| description | Triage Monte Carlo alerts interactively or build an automated workflow. Fetch, score, and troubleshoot alerts using MCP tools now, or design a reusable workflow that runs on a schedule. |
| category | Document Processing |
| source | antigravity |
| tags | ["mcp","ai","agent","automation","workflow","design","document","security"] |
| url | https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/automated-triage |
Monte Carlo Automated Triage
This skill helps you design, test, and deploy an automated triage agent for Monte Carlo alerts. Rather than a fixed workflow, it gives you the building blocks — a set of MCP tools, a description of each triage stage, and a working example — so you can build a process that matches how your team actually responds to alerts.
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.
Read the reference files before proceeding:
- Triage stages and customisation:
references/triage-stages.md (relative to this file)
- Working example workflow:
references/triage-example.md (relative to this file)
When to activate this skill
Activate when the user:
- Wants to triage or investigate recent Monte Carlo alerts (interactively or automated)
- Wants to set up automated triage for Monte Carlo alerts
- Asks to run agentic triage or investigate recent alert activity
- Wants to understand what triage tools are available and how to use them
- Is building or refining a triage prompt for their environment
- Wants to move from manual alert review to automated or semi-automated triage
When NOT to activate this skill
Do not activate when the user is:
- Investigating a specific known incident (help them directly)
- Creating or configuring monitors (use the monitoring-advisor skill)
- Running impact analysis before a code change (use the prevent skill)
Available MCP tools
All tools are available via the monte-carlo-mcp MCP server.
| Tool | Toolset | Purpose |
|---|
get_alerts | default | Fetch recent alerts for a time window |
alert_assessment | default | Score an alert by incident likelihood and potential impact (HIGH/MEDIUM/LOW each) |
run_troubleshooting_agent | default | Run the Monte Carlo Troubleshooting Agent on a single alert; async by default — returns immediately, reuses existing results when available |
get_troubleshooting_agent_results | default | Poll an async troubleshooting run by incident_id; returns status (not_found/running/success/failed) and results when complete |
update_alert | default | Update an alert's status and/or declare an incident by setting severity |
set_alert_owner | default | Assign an owner to an alert by email |
create_or_update_alert_comment | default | Post or update a triage comment on an alert |
mark_event_as_normal | default | Mark all anomaly events in an alert as normal, triggering ML threshold recalibration to prevent re-alerting on the same pattern |
How to approach automated triage
Read references/triage-stages.md for a full description of each stage and how to customise it. The high-level flow is:
- Fetch alerts — decide which alerts to triage and over what time window
- Initial investigation — score every alert by incident likelihood and potential impact using
alert_assessment
- Deep troubleshooting — run
run_troubleshooting_agent on high-signal alerts to get root cause analysis
- Classify — use the troubleshooting output to classify each alert
- Take actions — post comments, update statuses, message Slack, create tickets
The triage process is not fixed. Read the stages reference to understand the options and tradeoffs at each step, then design a workflow that fits your team's needs.
The longer-term direction
Most teams move through roughly the same arc, though the pace and path vary:
- Start with recommendations. Run manually and have the agent post comments describing what it found and what it would do — no actual status changes or external actions. Use this to tune the workflow until the output matches how your team would respond manually.
- Automate, still in recommendation mode. Once the output looks right, put it on a schedule. Keep it in recommendation mode while you validate it's behaving well on real traffic.
- **Replace recommendati
