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Found 776 Skills
Search and analyze DealerVision production logs via SolarWinds Observability API. Use when investigating errors, debugging issues, checking system health, or when the user mentions logs, SolarWinds, production errors, or system monitoring. Requires the `logs` CLI tool to be installed.
This skill should be used when users need to interact with AWS services via CLI. It covers all AWS services including EC2, ECS, EKS, Lambda, S3, RDS, DynamoDB, VPC, Route53, CloudFront, Bedrock, Support, Billing, and more. Supports querying, creating, modifying, deleting resources, monitoring, debugging, and cost analysis. Triggers on requests mentioning AWS, cloud resources, or specific AWS service names.
LLM cost tracking with Langfuse for cached responses. Use when monitoring cache effectiveness, tracking cost savings, or attributing costs to agents in multi-agent systems.
Creates comprehensive dashboard and analytics interfaces that combine data visualization, KPI cards, real-time updates, and interactive layouts. Use this skill when building business intelligence dashboards, monitoring systems, executive reports, or any interface that requires multiple coordinated data displays with filters, metrics, and visualizations working together.
Track Clawdbot AI model usage and estimate costs. Use when reporting daily/weekly costs, analyzing token usage across sessions, or monitoring AI spending. Supports Claude (opus/sonnet), GPT, and Codex models.
Health monitoring knowledge and procedures for infrastructure platforms. Use when assessing system health, running health audits, or setting up monitoring.
Track finance investment signal evolution and update logic based on new finance market information. Use when monitoring finance signals and determining if they are strengthened, weakened, or falsified.
Use when "deploying ML models", "MLOps", "model serving", "feature stores", "model monitoring", or asking about "PyTorch deployment", "TensorFlow production", "RAG systems", "LLM integration", "ML infrastructure"
Framework for monitoring activation, engagement, and monetization guardrails.
Optimize Databricks costs with cluster policies, spot instances, and monitoring. Use when reducing cloud spend, implementing cost controls, or analyzing Databricks usage costs. Trigger with phrases like "databricks cost", "reduce databricks spend", "databricks billing", "databricks cost optimization", "cluster cost".
Automate New Relic tasks via Rube MCP (Composio): APM, alerts, dashboards, NRQL queries, and infrastructure monitoring. Always search tools first for current schemas.
Observability and monitoring for data pipelines using OpenTelemetry (traces) and Prometheus (metrics). Covers instrumentation, dashboards, and alerting.