Skill UI

Checks website, GitHub, and local docs to identify messaging inconsistencies and captures version, feature, terminology, and contact differences in a read-only discrepancy report whenever a consistency check is requested.

Outlines WCAG 2.2 accessibility patterns for web apps, covering semantic HTML, ARIA roles, keyboard navigation, form handling, and contrast checks to keep interfaces usable for assistive technologies.

This skill provides comprehensive management for multiple local Command Line Interface (CLI) agents. It allows users to start, stop, monitor, and assign tasks to these agents, running them in separate tmux sessions for parallel execution. It is ideal for complex, scheduled workflows requiring multi-agent coordination, task monitoring, and log tailing, making it invaluable for advanced automation setups.

Utilizes the Azure AI Projects SDK's ImageBasedHostedAgentDefinition to build robust, container-based AI agents deployed in Azure AI Foundry. This workflow is essential for creating production-grade agents that require custom logic, precise resource allocation (CPU/Memory), and integration of advanced tools like code interpreters.

Analyzes application logs to spot slow requests, recurring errors, and resource warnings, helping troubleshoot performance issues and inform structured logging or monitoring improvements.

Analyzes application logs to spot slow requests, recurring errors, and resource warnings, helping troubleshoot performance issues and inform structured logging or monitoring improvements.

Automate Apify web scraping Actors inside Claude Code to run crawlers synchronously or asynchronously, manage datasets, inspect logs, create reusable tasks, and pull structured results without leaving your workflow.

This comprehensive guide sets up a robust and isolated local development environment for Apollo.io integrations. It covers essential steps including configuring sandbox API keys, implementing a Mock Service Worker (MSW) for reliable offline API mocking, setting up detailed request logging, and configuring Vitest for efficient local testing. Ideal for developers building and debugging complex, API-dependent features.

Implement comprehensive observability for Apollo.io API integrations. This skill provides structured instrumentation covering Prometheus metrics (request count, latency, rate limits, credits used), structured logging with PII redaction, and OpenTelemetry tracing. It ensures reliable tracking of API health, performance, and resource consumption.

This comprehensive tool provides an automated, multi-stage checklist for deploying Apollo.io integrations to a production environment. It validates crucial aspects including secure authentication (API keys, headers), system resilience (rate limiting, retry logic), observability (PII redaction, structured logging), and financial controls (credit tracking). Use this checklist before going live or when performing production system audits to ensure full compliance and stability.

A comprehensive, production-grade reference architecture for integrating with Apollo.io. It details a layered design encompassing API services, business logic, background job processing (e.g., lead enrichment), and data modeling, enabling the building of robust sales intelligence and CRM synchronization systems.

This module provides production-ready TypeScript patterns for interacting with the Apollo.io REST API. It implements critical best practices including type-safe client setup (using Zod), custom error handling, exponential backoff retry logic, asynchronous pagination, and rate-aware bulk processing. Use this when building reliable, scalable, and robust integrations with Apollo data.