Skill UI

A systematic checklist for launching Attio API integrations into a live production environment. It covers critical best practices for ensuring stability, including robust authentication, advanced error handling (exponential backoff, retries), rate limiting strategies, data integrity checks, health monitoring endpoints, and comprehensive rollback plans. Essential for reliable SaaS deployments.

This guide outlines best practices for configuring and securing Adobe API access across Development, Staging, and Production environments. It details the use of separate Developer Console projects, implementing least-privilege OAuth scopes, and integrating robust secret management solutions (GCP Secret Manager, AWS Secrets Manager, HashiCorp Vault) into CI/CD pipelines for secure, scalable deployments.

A comprehensive guide and toolkit for Amazon Aurora DSQL, a serverless, PostgreSQL-compatible distributed SQL database. Covers advanced topics including schema management, multi-tenant patterns, complex DDL migrations (e.g., column operations, constraint changes), migration from MySQL, IAM authentication, and detailed query plan analysis (EXPLAIN ANALYZE). Use this skill for full lifecycle database development.

A comprehensive guide for deploying Attio-powered applications to major production platforms including Vercel, Fly.io, Cloud Run, and Railway. This guide covers essential DevOps practices such as secure secrets injection, robust health check endpoints, webhook URL configuration, and platform-specific deployment commands to ensure reliable, production-grade integration.

This guide outlines security best practices for managing Bright Data zone credentials, API tokens, and webhooks. It covers crucial steps like credential inventory, environment variable security, zone isolation across environments, scheduled credential rotation, and implementing pre-commit hooks to prevent sensitive data leakage, maximizing data security and compliance.

A comprehensive provider for integrating Eufy security cameras (supporting local P2P or cloud connectivity). This tool facilitates stable RTSP streaming for live monitoring and efficiently captures event-triggered video clips. It is designed for advanced systems that require continuous video feeds and reliable event-based data input for AI analysis and monitoring solutions.

A comprehensive, multi-phase checklist for deploying and validating CAST AI cost optimization and autoscaling features on a production Kubernetes cluster. It guides users through prerequisites, initial monitoring setup (Phase 1), full autoscaling enablement (Phase 2), security hardening (RBAC, secrets), and critical validation commands for safe go-live deployment.

This skill performs comprehensive, systematic cleanup across 11 critical dimensions of code quality, including dead code removal, security vulnerability checks, weak type elimination, and performance optimization. It analyzes code, assigns confidence scores, and verifies all suggested changes using build and test gates. Ideal for projects suffering from accumulated technical debt, or before major release cycles to ensure robust, maintainable code.

A comprehensive, step-by-step runbook designed for diagnosing and resolving critical operational issues in ClickHouse databases. Covers tiered severity levels (P1-P3) for scenarios ranging from server outages and OOM kills to performance degradation and stuck queries. Provides essential system tables queries and commands for service recovery and system health checks.

This comprehensive guide details how to set up end-to-end observability for ClickHouse. It covers extracting key metrics using built-in system tables (e.g., query logs, merge status), integrating the metrics with Prometheus, and finally visualizing performance, throughput, and health indicators on Grafana dashboards. Essential for monitoring production-grade ClickHouse deployments and configuring reliable alerting.

This runbook provides structured steps for responding to critical production incidents on the CoreWeave platform. Use it when dealing with GPU workload failures, inference service outages, or general Kubernetes resource issues. It guides users through checking pod status, node health, and diagnosing common model loading errors to ensure rapid service recovery.

This guide provides a comprehensive framework for investigating production issues on the Nexu platform using the Datadog Logs API. It details how to query crash events, analyze OpenClaw stderr output, check gateway startup status, and review API request logs (including 5xx errors). It includes best practices for authentication, filtering by pod/time, and parsing raw JSON logs using Python for actionable insights.