What problem does it solve? Designing observability for a service from scratch is slow and error-prone: teams struggle to pick the right SLIs, set realistic SLO targets, tame noisy alerts, and build dashboards that actually help during incidents. This Skill automates that design work with three Python scripts. ## Core Features & Use Cases - SLO Designer: Generates SLI definitions, SLO targets, error budgets, and multi-window burn rate alerts from a service definition (type, criticality, user-facing status). - Alert Optimizer: Analyzes existing alert configurations to detect noisy alerts, duplicate rules, coverage gaps against the golden signals, and alert fatigue risk, then emits an optimized configuration. - Dashboard Generator: Produces Grafana-compatible dashboard JSON with role-based layouts (SRE, developer, executive, ops), golden signals panels, and drill-down paths. - Use Case: When onboarding a new payment API, generate its SLO scaffold, import a ready-made Grafana dashboard, and run your existing Prometheus alert rules through the optimizer to cut false positives before the next on-call rotation. ## Quick Start Ask the AI to generate an SRE dashboard and optimized alert configuration for your service by running the dashboard_generator.py and alert_optimizer.py scripts with your service definition JSON.
