Skill UI

Provides comprehensive strategies for handling external API rate limits (HTTP 429 errors). This skill implements advanced patterns including exponential backoff with jitter, request queuing, and header monitoring. It is crucial for building reliable, high-throughput integrations with rate-limited services like ClickUp.

Provides a production-ready, layered architectural guide for integrating with the ClickUp API v2. This comprehensive reference covers implementing core features such as custom fields, detailed time tracking, goal setting (OKRs), and robust two-way synchronization with external systems. It is essential reading for developers building sophisticated, enterprise-grade ClickUp solutions.

A comprehensive guide to securing ClickUp API usage. Learn best practices for managing API tokens, implementing least-privilege access, and auditing usage patterns. This includes secure token rotation procedures, using environment variables, setting up pre-commit hooks to prevent leaks, and structuring calls for robust audit logging.

This skill provides a comprehensive framework for conducting high-quality code reviews. It guides developers through checking code across four critical dimensions: Correctness (functional accuracy and edge cases), Maintainability (readability and documentation), Performance (efficiency and resource usage), and Security (input validation and vulnerability management). It also emphasizes providing actionable, constructive, and empathetic feedback.

This expert skill converts static or modern frameworks (React, Next.js, HTML) into fully dynamic, pixel-perfect, and SEO-optimized WordPress themes. It functions as a senior architect, ensuring absolute fidelity to the source while integrating core WordPress functionalities like ACF, custom hooks, and technical SEO best practices. Ideal for large-scale website migrations.

This guide details how to use sophisticated coding agents (such as Codex, Claude Code, or Pi) through a structured bash workflow. It provides methods for complex development tasks, including building new features, refactoring large codebases, and reviewing pull requests (PRs). Key best practices covered include managing pseudo-terminals (PTY), defining focused working directories (`workdir`), and executing tasks in the background for robust, multi-step automation.

A comprehensive guide to configuring robust CI/CD pipelines for Cohere API v2 applications. This skill covers setting up automated unit tests (mocked responses) and critical integration tests (real API calls) within environments like GitHub Actions. It ensures the stability and reliability of Cohere-powered features such as Chat, Embeddings, and Rerank across development cycles.

This comprehensive runbook provides structured procedures for handling Cohere API outages. It guides users through incident triage (P1-P4), quick troubleshooting steps, and detailed mitigation strategies for common error codes (401, 429, 5xx). Includes best practices for graceful degradation and post-incident review, ensuring rapid service restoration.

This guide sets up a comprehensive, fast, and reproducible local development workflow for integrating with the Cohere API v2. It utilizes mocking, vitest for unit testing, and hot reload capabilities (tsx watch) to ensure rapid iteration cycles without constant reliance on external APIs. Ideal for developers building AI applications with Cohere.

A comprehensive guide for configuring and integrating the Cohere API v2 across development, staging, and production environments. This pattern ensures environment-specific settings—including API keys, model selections, token limits, and caching strategies—are correctly applied. It covers best practices for secure secret management using tools like Vault, AWS Secrets Manager, and GCP Secret Manager, ensuring robust and scalable deployments.

A comprehensive solution for setting up production-grade observability for Cohere API v2. It integrates Prometheus metrics, OpenTelemetry tracing, and robust alerting mechanisms. This skill tracks critical operational data including per-endpoint latency, token consumption (input/output), error rates, and usage costs, ensuring reliable monitoring for AI-powered applications.

This guide details advanced patterns for managing API rate limits, particularly for external AI services like Cohere. It covers implementing exponential backoff with jitter for handling transient 429 errors, utilizing concurrency-limited request queues, and building proactive rate limit trackers. These techniques ensure highly reliable and optimized API throughput in production systems.