mlops-monitoring-drift
SKILL.md
Mlops Monitoring Drift
Overview
Use this skill to detect meaningful model degradation early and trigger appropriate remediation actions.
Scope Boundaries
- Use this skill when the task matches the trigger condition described in
description. - Do not use this skill when the primary task falls outside this skill's domain.
Shared References
- Drift alerting and escalation rules:
references/drift-alerting-escalation-rules.md
Templates And Assets
- Drift monitoring policy template:
assets/drift-monitoring-policy-template.md
Inputs To Gather
- Drift signals and quality metrics to monitor.
- Alert thresholds and acceptable noise level.
- Escalation owners and response SLA.
- Retraining and rollback policies.
Deliverables
- Drift monitoring policy and thresholds.
- Alert routing and severity model.
- Response playbook for drift events.
Workflow
- Define monitoring policy in
assets/drift-monitoring-policy-template.md. - Validate threshold actionability via
references/drift-alerting-escalation-rules.md. - Test alert behavior with historical replay or backtests.
- Assign response ownership and SLA per severity.
- Publish retraining/mitigation decision criteria.
Quality Standard
- Alerts are actionable, not noise-heavy.
- Severity levels map to clear response ownership.
- Retraining triggers are explicit and auditable.
Failure Conditions
- Stop when drift thresholds are not operationally actionable.
- Stop when alerts have no clear owner.
- Escalate when degradation risk remains unmanaged.
Weekly Installs
5
Repository
kentoshimizu/sw…t-skillsGitHub Stars
4
First Seen
14 days ago
Security Audits
Installed on
cline5
github-copilot5
codex5
kimi-cli5
gemini-cli5
cursor5