Oncall Irm logo

Oncall Irm

Organization
grafana
oncall-irm

Route alerts, run on-call rotations, and drive incidents in Grafana IRM / OnCall — integrations (Alertmanager / Grafana Alerting / generic webhook / PagerDuty), Jinja2 routing + grouping templates, escalation chains (wait → notify schedule → notify team → webhook → auto-resolve), schedules (web + iCal + Terraform `grafana_oncall_schedule`), Slack chatops with Acknowledge/Resolve/Silence, and the P1-P4 incident lifecycle. Use when wiring Alertmanager to OnCall, deciding which team gets paged, building rotations from a Google Calendar / iCal, hooking up Slack notifications, or declaring an incident from an alert — even when the user says "page the platform team on critical alerts", "send Prometheus alerts to Slack", "set up our on-call rota", "escalation policy", or "auto-resolve when the alert clears" without naming OnCall / IRM. Heads up — OnCall OSS is in maintenance mode (archived March 2026); Grafana Cloud users should use IRM.

Overview

Publishergrafana
Repositoryskills
Skill nameoncall-irm
Stars
289
Forks
27
Bundled files
2
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by grafana on GitHub. Read the source before you install it.

Installation

Install the Oncall Irm AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/grafana/skills/tree/main/skills/grafana-cloud/oncall-irm
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/grafana/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/grafana-cloud/oncall-irm .claude/skills/oncall-irm
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Oncall Irm in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Oncall Irm on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Oncall Irm is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Grafana OnCall & IRM

OnCall docs: https://grafana.com/docs/oncall/latest/ IRM docs: https://grafana.com/docs/grafana-cloud/alerting-and-irm/

Grafana OnCall OSS is in maintenance mode (archived March 2026). Cloud users → IRM. Concepts (chains, schedules, integrations) are identical.

Prerequisites

  • Grafana Cloud stack with IRM/OnCall enabled
  • API token (Authorization: <token>)
  • Slack workspace + admin to install the OnCall app (for ChatOps)

Core concepts

ConceptDescription
IntegrationWebhook URL accepting alerts; one per source
RouteJinja2 condition that maps to an escalation chain (first True wins)
Escalation ChainWait / notify schedule / notify team / webhook / auto-resolve steps
ScheduleCalendar-based rotation (web / iCal / Terraform)
Alert GroupRelated alerts collapsed by a Grouping ID template
Notification PolicyPer-user channels — Slack, mobile push, SMS, phone, email

Flow: alert → integration → routing template → escalation chain → notifications → ack / resolve.

Common Workflows

1. Wire Alertmanager → IRM and verify routing

yaml
# 1. In IRM: New integration → Alertmanager. Copy the webhook URL.
# 2. alertmanager.yml (see references/integrations.md for full block):
receivers:
  - name: grafana-oncall
    webhook_configs:
      - url: https://<stack>.grafana.net/integrations/v1/alertmanager/<id>/
        send_resolved: true
        max_alerts: 100
bash
# 3. Test the routing template BEFORE going live (UI: Integration → Route → "Preview")
#    Paste a sample payload (use a real Alertmanager test webhook). Expect:
#      Routing result: True
#      Escalation chain selected: <expected chain>
#    If False — your Jinja expression is wrong; fix and re-preview.

# 4. End-to-end test — fire amtool (or any test webhook) at the URL
amtool alert add foo severity=critical team=platform --alertmanager.url http://localhost:9093

# 5. Verify in IRM → Alert Groups (should appear within ~5s) — confirm:
#    - Correct route fired
#    - Correct schedule/user notified
#    - Slack message appeared in the configured channel

Routing template syntax + Jinja helpers: references/templates-schedules.md. Other integrations (Grafana Alerting, generic webhook, Slack): references/integrations.md.

2. Build an escalation chain + verify

1. Notify "Primary On-Call" (Important Notifications)
2. Wait 5 min
3. Notify "Primary On-Call" (Default Notifications)
4. Wait 10 min
5. Notify team "Platform"
6. Trigger outgoing webhook (PagerDuty / ticket)
bash
# Verify: create a test alert (UI → Integration → "Send demo alert"),
# then watch the alert-group timeline tick through steps 1 → 6.
# Use IRM → Escalation Chains → "Test" if available, otherwise the demo alert is the canonical check.

3. Create a schedule from iCal + verify "who is on-call right now"

bash
# 1. Create the schedule
curl -X POST https://<stack>.grafana.net/api/v1/schedules/ \
  -H "Authorization: <token>" -H "Content-Type: application/json" \
  -d '{"name":"Platform On-Call",
       "ical_url_primary":"https://calendar.example.com/platform.ics",
       "slack":{"channel_id":"C123456ABC","user_group_id":"S123456ABC"}}'

# 2. Verify the schedule was created
curl -s https://<stack>.grafana.net/api/v1/schedules/ \
  -H "Authorization: <token>" | jq '.results[] | select(.name=="Platform On-Call")'

# 3. Verify who is on-call right now
curl -s https://<stack>.grafana.net/api/v1/schedules/<schedule_id>/next_shifts/ \
  -H "Authorization: <token>" | jq '.results[0]'
# Expect a shift starting now (or recently) with the right user_id.

Terraform variant + shift block: references/templates-schedules.md.

Best practices

  • Keep chains ≤4 levels with a definitive final step (webhook to PagerDuty or auto-resolve)
  • Always set send_resolved: true in Alertmanager so OnCall auto-resolves
  • Use max_alerts: 100 in Alertmanager webhook config
  • Combine Slack + mobile push for delivery reliability
  • Assign integrations/schedules to teams for RBAC

Resources

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Oncall Irm AI skill do?

Route alerts, run on-call rotations, and drive incidents in Grafana IRM / OnCall — integrations (Alertmanager / Grafana Alerting / generic webhook / PagerDuty), Jinja2 routing + grouping templates, escalation chains (wait → notify schedule → notify team → webhook → auto-resolve), schedules (web + iCal + Terraform `grafana_oncall_schedule`), Slack chatops with Acknowledge/Resolve/Silence, and the P1-P4 incident lifecycle. Use when wiring Alertmanager to OnCall, deciding which team gets paged, building rotations from a Google Calendar / iCal, hooking up Slack notifications, or declaring an in...

Why use Oncall Irm on TypingMind?

Because you install it once and use it with any model. Oncall Irm is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Oncall Irm in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/grafana/skills/tree/main/skills/grafana-cloud/oncall-irm. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Oncall Irm?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Oncall Irm?

As many as you like. As long as a model supports skills, you can use Oncall Irm with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Oncall Irm AI skill free?

Yes. It is published on GitHub by grafana under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇