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Found 350 Skills
Deploys and operates containerized workloads on ECS, Fargate, and ECR. Covers task definitions, Fargate services, ECR repository setup and lifecycle policies, ECS Exec debugging, service scaling, deployment strategies, load balancer integration, and logging configuration. Use when deploying, debugging, or optimizing containers on AWS. ALSO USE for container deployment options (ECS vs ECS Express Mode), networking modes, health check troubleshooting, OOM errors, secrets injection, blue/green deployments, ECR image management, and App Runner sunset guidance and migration. NOT for Kubernetes, EKS, or CI/CD pipelines.
Builds, configures, debugs, and optimizes AWS observability using CloudWatch (Logs Insights, Metrics, Alarms, Dashboards, EMF), X-Ray, CloudTrail, and ADOT. Covers Log Insights query syntax (fields, filter, stats, parse, pattern, join, subqueries), alarm configuration (metric, composite, anomaly detection, missing data treatment), dashboard design, custom metrics (PutMetricData, EMF, metric filters), X-Ray tracing (ADOT, sampling rules, annotations vs metadata), ADOT collector config, and CloudTrail auditing. Use when the user mentions CloudWatch, Log Insights, alarms, INSUFFICIENT_DATA, dashboards, custom metrics, EMF, X-Ray, traces, sampling, CloudTrail, who deleted, ADOT, OpenTelemetry, observability, monitoring, synthetics, canaries, or troubleshooting alarm behavior. Do NOT use for application logging setup, container log drivers, or security threat detection.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
Use this as the main Claude Scholar skill for a vault-first, project-scoped Obsidian research knowledge base rooted at Research/{project-slug}/. It owns bootstrap, routing, daily logging, hub/plan/index maintenance, registry updates, lifecycle actions, and lint orchestration.
How to create topics, submit messages, and subscribe to real-time message streams on Hedera using the Hiero JavaScript SDK (@hiero-ledger/sdk). Use this skill whenever the user wants to work with Hedera Consensus Service (HCS), including topic creation, message submission, pub/sub messaging, mirror node subscriptions, chunked large messages, topic fees, or any consensus-related operation in JavaScript or TypeScript. Also trigger when users mention @hashgraph/sdk topic operations, event logging on Hedera, decentralized messaging, audit trails, or ordered message streams.
Schema for tracking code review outcomes to enable feedback-driven skill improvement. Use when logging review results or analyzing review quality.
Comprehensive Go error handling patterns from Google and Uber style guides. Covers returning errors, wrapping with %w, sentinel errors, choosing error types, handling errors once, error flow structure, and logging. Use when writing Go code that creates, returns, wraps, or handles errors.
Automatically discover observability and monitoring skills when working with Prometheus, Grafana, distributed tracing, structured logging, metrics, alerting, dashboards, or monitoring. Activates for observability development tasks.
nginx C module performance optimization and reliability guidelines based on the official nginx development guide. This skill should be used when optimizing nginx C modules for throughput, latency, memory efficiency, and operational resilience. Triggers on tasks involving buffer optimization, connection tuning, shared memory contention, error recovery, timeout strategy, caching implementation, worker process tuning, or logging performance in nginx C modules.
Set up comprehensive observability for Databricks with metrics, traces, and alerts. Use when implementing monitoring for Databricks jobs, setting up dashboards, or configuring alerting for pipeline health. Trigger with phrases like "databricks monitoring", "databricks metrics", "databricks observability", "monitor databricks", "databricks alerts", "databricks logging".
Use when adding logging to services, setting up monitoring, creating alerts, debugging production issues, designing SLIs/SLOs, or implementing structured logging (Pino, Winston), metrics (Prometheus, DataDog, CloudWatch), or distributed tracing (OpenTelemetry).
Designs and outputs n8n workflow JSON with robust triggers, idempotency, error handling, logging, retries, and human-in-the-loop review queues. Use when you need an auditable automation that won’t silently fail.