usage-health-scorecard
Framework for monitoring activation, engagement, and monetization guardrails.
Works with
--- name: usage-health-scorecard description: Framework for monitoring activation, engagement, and monetization guardrails. license: Apache-2.0 --- # Usage Health Scorecard Skill ## When to Use - Tracking activation/retention metrics for self-serve and hybrid customer cohorts. - Monitoring the impact of PLG experiments on core product health. - Sharing health snapshots with product, growth, and CS leads. ## Framework 1. **Metric Groups** – activation, engagement, collaboration, monetization, support load. 2. **Segmentation** – persona, plan, cohort, region, product area. 3. **Thresholds** – traffic light ranges for each metric with warning/critical bands. 4. **Alerting** – notification rules for drops, anomalies, or experiment impacts. 5. **Action Registry** – log remediation steps, owners, due dates, and results. ## Templates - Scorecard layout (metric, current, target, delta, owner). - Dashboard wireframe with spark lines + annotations. - Action tracker for follow-up tasks linked to health changes. ## Tips - Pair with `launch-in-app-experiments` to watch guardrails post-launch. - Include qualitative signals (support tags, NPS) to contextualize telemetry. - Archive snapshots to tell longitudinal stories in QBRs. ---
More Observability skills
google-agents-cli-observability
google/agents-cli
>
azure-observability
microsoft/azure-skills
Azure Observability Services including Azure Monitor, Application Insights, Log Analytics, Alerts, and Workbooks. Provides metrics, APM, distributed tracing, KQL queries, and interactive reports. USE FOR: Azure Monitor, Application Insights, Log Analytics, Alerts, Workbooks, metrics, APM, distributed tracing, KQL queries, interactive reports, observability, monitoring dashboards. DO NOT USE FOR: instrumenting apps with App Insights SDK (use appinsights-instrumentation), querying Kusto/ADX clusters (use azure-kusto), cost analysis (use azure-cost-optimization).
workers-best-practices
cloudflare/skills
Reviews and authors Cloudflare Workers code against production best practices. Load when writing new Workers, reviewing Worker code, configuring wrangler.jsonc, or checking for common Workers anti-patterns (streaming, floating promises, global state, secrets, bindings, observability). Biases towards retrieval from Cloudflare docs over pre-trained knowledge.

