AI AGENTS
Incumbent License + Card Watch -> PagerDuty Alert
Monitors the model card of the open model you already run in production and pages on-call via PagerDuty the moment its license, usage restrictions, or deprecation status changes…
How it runs
The automated pipeline, trigger to output.
- TriggerSchedule checks incumbent card
- ActionRead incumbent license + status fieldsHugging Face
- LogicAdverse license/deprecation change?
- ActionAssemble incident summary with field diff
- OutputOpen PagerDuty incident + Slack notePagerDuty
What it does
Protects you from your incumbent model changing terms under you. It watches the live model card of the model already in production and detects a license downgrade, new usage restriction, gating, or deprecation notice — then raises a PagerDuty incident so on-call can react before it becomes a compliance or outage problem.
When to use it
Use it when you depend on a specific open model and a license or availability change would be a real business risk. This is a defensive watcher on the model you run, not a hunt for better challengers.
How it works
- 1A schedule checks the incumbent's HuggingFace card on a tight cadence.
- 2The agent compares the current license, gating, and deprecation fields to the last known snapshot.
- 3A branch fires only on adverse changes: more restrictive license, new gate, or deprecation.
- 4It assembles an incident summary with the exact field diff and the affected services.
- 5It opens a PagerDuty incident at the configured severity for on-call.
- 6It posts the same summary to the model-ops Slack channel for visibility.
Set it up
What you configure once, before turning it on.
- 1Connect Hugging FaceModels, datasets, spaces — the open-source hub.
- 2Connect PagerDutyIncidents, on-call, escalations.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More AI Agents workflows
Stale Doc-PR Chaser for Runbook Gaps
On a daily schedule the agent finds runbook doc PRs that were opened from resolved incidents but never reviewed, summarizes what each one fixes.
On-Call Runbook Gap Closer: Resolved Sentry Issues to Doc PRs
An agent reads each newly resolved Sentry issue, compares the actual fix against your existing runbook, and opens a GitHub PR adding the missing remediation steps.
Datadog Bill Spike Attribution Agent
When a daily Datadog cost check detects a spend jump, an agent attributes the increase to the specific services and metric types driving it and posts a ranked breakdown to Slack.
Sentry-to-Confluence Runbook Updater
When a Sentry issue is resolved, the agent finds the matching Confluence runbook page and proposes an inline update with the verified fix.
Custom Metrics Cardinality Spike Pager
A webhook from a Datadog monitor fires when custom-metric cardinality jumps; an agent pinpoints the offending metric and tag, estimates the added cost.
Resolved Incident to Public Troubleshooting Doc
For customer-facing errors resolved in Sentry, the agent drafts a sanitized troubleshooting entry and opens a PR to your ReadMe documentation.
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.

Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.
