Skill UI

This skill provides a comprehensive diagnostic reference for common errors and exceptions encountered with the Instantly.ai API v2. It covers critical areas including HTTP status codes (400, 401, 429, 500), campaign lifecycle issues (e.g., stuck in draft), account health checks, lead duplication handling, and implementing rate limit backoff. Use this when debugging failed API requests or troubleshooting complex campaign, account, or lead management issues.

This guide provides a comprehensive reference for diagnosing and resolving common errors encountered when interacting with the Kling AI API. It covers various HTTP status codes (e.g., 400, 401, 429), task-level failures (e.g., content policy violations, low image quality), proper JWT token management, and implementing rate limit handling with exponential backoff. Use this resource when troubleshooting failed video generation or API integration issues.

A comprehensive guide detailing how to set up secure API authentication for Kling AI using JSON Web Tokens (JWT). This process involves generating tokens from your Access Key (AK) and Secret Key (SK) credentials, providing code examples for Python and Node.js, and implementing best practices for token management and refreshing to ensure continuous API access.

Automated guidance for Kubernetes service management in the DevOps Advanced domain, offering best-practice advice, code snippets, and config checks for services, Terraform, Helm, and monitoring workflows.

This skill integrates Continuous Integration/Continuous Deployment (CI/CD) pipelines with Linear issue tracking. It automatically detects deployment URLs (e.g., Vercel, Railway), adds detailed deployment comments to relevant Linear issues, and manages state transitions (e.g., moving an issue to 'Review' or 'Done') based on the deployment environment (staging or production). It ensures a seamless link between code commits, deployment status, and project management tickets.

A comprehensive guide to integrating Lokalise into Continuous Integration/Continuous Deployment (CI/CD) workflows using GitHub Actions. This setup automates the entire translation lifecycle: uploading source strings on code pushes, downloading the latest translations during builds, and running PR checks to ensure translation coverage across all required locales. It eliminates manual file management, keeping code, translations, and CI pipelines perfectly synchronized.

This comprehensive script suite provides a structured, multi-step audit for internationalization (i18n) integrations using Lokalise. It automates crucial checks, including verifying translation coverage across all required locales, detecting key synchronization issues (missing or orphaned keys) between the source code and the Translation Management System (TMS), and validating the format of localized files. Use this utility before any major production deployment or go-live phase to ensure localization readiness.

Helps manage container registries like AWS ECR, Google GCR, and Harbor by generating configuration code, guiding access controls, and advising best practices for secure, production-ready image storage and deployment automation.

Provides cross-language patterns for developing memory-safe systems code. This skill covers crucial concepts like RAII, ownership models, smart pointers, and robust resource management. It is essential for preventing common vulnerabilities such as use-after-free, memory leaks, and ensuring reliable resource handling across complex systems.

This comprehensive checklist guides the safe and robust deployment of Mistral AI integrations to a production environment. It covers critical operational steps, including secure credential management, rigorous code quality gates, establishing health endpoints, implementing circuit breakers for resilience, executing gradual rollouts, and defining emergency rollback procedures to ensure system stability and high availability.

A comprehensive skill for building and maintaining efficient, scalable monorepositories. This involves strategies for enabling code sharing, ensuring consistent tooling across multiple packages and applications, and managing atomic changes. Use this skill for setting up new monorepo architectures, migrating existing repositories, and optimizing complex CI/CD pipelines.

This comprehensive guide provides developers with step-by-step instructions for migrating applications from direct calls to proprietary Large Language Model (LLM) APIs (such as OpenAI or Anthropic) to utilizing the unified OpenRouter gateway. It details essential code changes, including updating base URLs, managing API keys, adding custom headers, and correctly prefixing model identifiers. This ensures a seamless transition, enabling multi-model compatibility and simplified API management.