Skill UI

Develop a complete, multi-chain wallet portfolio tracker using Alchemy's Enhanced APIs. This workflow aggregates ETH balances, ERC-20 token holdings, NFT assets (ERC-721/1155), and transaction history across major chains (Ethereum, Polygon, Arbitrum, Optimism, Base). Ideal for building sophisticated decentralized applications (dApps) and comprehensive Web3 dashboards.

A comprehensive, multi-chain reference architecture for building robust decentralized applications (dApps) powered by Alchemy. This guide outlines the full stack, from the React/Next.js frontend and API layer to core blockchain interactions, incorporating best practices like rate limiting, caching, and secure API proxying. Ideal for planning complex, production-grade Web3 systems across multiple chains (ETH, Polygon, etc.).

This guide demonstrates how to implement tool use (function calling) with Claude's Messages API. It covers defining structured tools using JSON Schema, handling tool calls, executing the corresponding code, and feeding the results back to create sophisticated, multi-step AI agents and complex workflows.

This comprehensive guide teaches developers how to interact with Claude AI using the official Anthropic SDK. It provides step-by-step instructions on basic message creation, implementing system prompts, and managing multi-turn conversation flows via the Messages API. Ideal for setting up a new Claude integration or testing core API functionality.

Builds a robust, automated workflow to export critical sales data—including forecasts, quota details, adjustments, and CRM totals—from Clari CRM to a designated data warehouse. The pipeline supports multiple targets like Snowflake, BigQuery, and PostgreSQL, ensuring that real-time revenue intelligence is available for advanced analytics and business reporting.

Learn how to build complex, multi-step AI agents using Cohere's Chat API v2. This skill demonstrates defining external tools (like weather APIs or database searches) and implementing the full agent loop: model calls tool -> execute tool -> feed result back -> final answer. Ideal for creating autonomous, tool-using workflows that interact with external systems.

This skill performs comprehensive regulatory gap analysis across major compliance frameworks, including GDPR, CCPA, ADA, PCI-DSS, and CAN-SPAM. It analyzes live websites and codebases to produce a detailed compliance scorecard, identifies specific non-compliant gaps, and generates a prioritized remediation roadmap with effort estimates. Essential for businesses ensuring legal adherence across multiple global jurisdictions.

This advanced skill orchestrates a comprehensive, multi-agent review of legal contracts. It analyzes risk, compliance, missing protections, and plain-English readability simultaneously. By simulating a team of legal specialists, it aggregates findings into a single executive report, complete with a quantifiable Contract Safety Score (0-100). Ideal for founders, freelancers, or small businesses needing expert legal insights without retaining full-time counsel.

This guide details how to set up and execute large-scale, distributed GPU training jobs on the CoreWeave platform. It covers both single-node multi-GPU setups and multi-node training utilizing PyTorch DDP and Kubernetes resources (A100/H100). This workflow is ideal for fine-tuning large language models (LLMs) or running complex deep learning models that require high-performance, shared-storage compute clusters.

This skill provides comprehensive guidance for deploying and managing GPU-accelerated AI inference services on CoreWeave Kubernetes (CKS). It covers best practices including containerization using NVIDIA CUDA base images, configuring specific GPU resource limits (A100/H100), setting up robust health checks, and executing controlled rolling updates. Ideal for managing multi-model inference and scaling demanding AI workloads in a cloud environment.

This skill outlines how to implement and manage Role-Based Access Control (RBAC) and namespace isolation for multi-team GPU workloads running on CoreWeave's Kubernetes platform. It provides guidance on setting strict resource quotas, preventing noisy-neighbor issues, and defining granular roles (e.g., ML Engineer, Inference Operator). This is essential for maintaining resource isolation, ensuring compliance (SOC 2, HIPAA), and managing access across large-scale cloud deployments.

This guide details setting up and managing CoreWeave GPU cloud infrastructure across Development, Staging, and Production environments. It ensures strict resource separation using dedicated Kubernetes namespaces for GPU quotas and scaling policies. Use this when deploying complex ML/AI workloads requiring robust environment isolation and controlled promotion workflows.