Loading...
Loading...
Found 675 Skills
AWS CloudFormation patterns for CloudWatch monitoring, metrics, alarms, dashboards, logs, and observability. Use when creating CloudWatch metrics, alarms, dashboards, log groups, log subscriptions, anomaly detection, synthesized canaries, Application Signals, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references, and CloudWatch best practices for monitoring production infrastructure.
Monitoring guidelines for applications and infrastructure including metrics collection, alerting strategies, and SLO-based monitoring
Filter and screen stocks by financial metrics like P/E ratio, market cap, dividend yield, and growth rates. Analyze and compare stocks from CSV data.
Write structured product requirements documents (PRDs) with problem statements, user stories, requirements, and success metrics. Use when speccing a new feature, writing a PRD, defining acceptance criteria, prioritizing requirements, or documenting product decisions.
Comprehensive observability and monitoring skill covering Prometheus, Grafana, metrics collection, alerting, exporters, PromQL, and production monitoring patterns for distributed systems and cloud-native applications
Define, track, and analyze product metrics with frameworks for goal setting and dashboard design. Use when setting up OKRs, building metrics dashboards, running weekly metrics reviews, identifying trends, or choosing the right metrics for a product area.
Expert growth product management guidance for SaaS applications. Use when designing growth loops, optimizing activation and onboarding, building retention systems, creating referral mechanics, running growth experiments, defining north star metrics, or implementing PLG strategies. Covers the full growth lifecycle from acquisition to monetization.
Token-Oriented Object Notation (TOON) format expert for 30-60% token savings on structured data. Auto-applies to arrays with 5+ items, tables, logs, API responses, database results. Supports tabular, inline, and expanded formats with comma/tab/pipe delimiters. Triggers on large JSON, data optimization, token reduction, structured data, arrays, tables, logs, metrics, TOON.
Lean Startup methodology based on Eric Ries' "The Lean Startup". Use when you need to: (1) design MVP scope for new product ideas, (2) define validated learning experiments, (3) create innovation accounting frameworks, (4) decide when to pivot vs. persevere, (5) set up metrics that matter vs. vanity metrics, (6) reduce product development waste, (7) apply scientific method to entrepreneurship, (8) test business model assumptions quickly.
Full-stack observability with Datadog APM, logs, metrics, synthetics, and RUM. Use when implementing monitoring, tracing, alerting, or cost optimization for production systems.
Calculate and interpret revenue, retention, and growth metrics for SaaS products. Covers revenue, ARPU/ARPA, MRR/ARR, churn, NRR, expansion, and cohort analysis.
Collect and analyze on-device performance metrics and crash diagnostics using MetricKit. Use when setting up MXMetricManager, handling MXMetricPayload or MXDiagnosticPayload, processing crash/hang/disk-write diagnostics via MXCallStackTree, adding custom signpost metrics, or uploading telemetry to an analytics backend.