Skill UI

This tool provides comprehensive on-chain analysis for DeFi protocols, allowing users to track metrics like Total Value Locked (TVL), fee revenue, DEX volumes, and yield opportunities. It is essential for DeFi researchers, protocol analysts, and yield farmers who require programmatic access to deep blockchain insights using the DeFiLlama API.

This tool provides comprehensive on-chain analysis for DeFi protocols, allowing users to track metrics like Total Value Locked (TVL), fee revenue, DEX volumes, and yield opportunities. It is essential for DeFi researchers, protocol analysts, and yield farmers who require programmatic access to deep blockchain insights using the DeFiLlama API.

A comprehensive workflow for executing advanced, semantic web searches using Exa. This tool moves beyond simple keyword matching, enabling deep context retrieval by understanding the intent behind the query. Key features include RAG context retrieval, content extraction (summaries, highlights, full text), and robust filtering by date range, specific domains, and content categories. Ideal for building knowledge base search features and complex research pipelines.

A comprehensive tool for querying and analyzing deep blockchain data across multiple EVM-compatible networks, including Ethereum, Polygon, Arbitrum, and Optimism. It supports tracking transactions by hash, checking address balances, inspecting blocks, and resolving ERC-20 token holdings. Ideal for crypto analysts, developers, and researchers requiring programmatic, detailed insights into on-chain financial activity and protocol interactions.

This advanced workflow enables users to perform deep analyses on large-scale people intelligence datasets. Users can build custom queries with multi-dimensional filters, run comparisons across different candidate pools (e.g., Q1 vs Q4), and aggregate skill density by geographical region. It is essential for talent acquisition teams needing to identify market trends and optimize hiring strategies beyond standard search functions.

A comprehensive workflow utilizing the Perplexity Sonar API for advanced, multi-turn research. It systematically decomposes broad topics into focused sub-queries, executes batch queries while maintaining context continuity, deduplicates citations, and synthesizes all findings into a structured, comprehensive research document. Ideal for academic research, market analysis, and generating detailed investment or industry briefs.

This skill provides comprehensive capabilities for web searching, content extraction, and web crawling using the Tavily API. It is ideal for tasks requiring up-to-date information retrieval, deep content scraping from specific URLs, or comprehensive website crawling for research purposes, making it a powerful research augmentation tool.

Molfeat is a Python toolkit that converts SMILES/RDKit molecules into embeddings via 100+ calculators, transformers, and pretrained models for QSAR, screening, similarity search, and deep learning pipelines.

A comprehensive toolkit designed for advanced data scraping and automation workflows on X/Twitter. Capabilities include deep tweet search, user profile analysis, bulk follower/media export, automated posting (replies, DMs), real-time account monitoring via webhooks, and integration with multiple AI agent platforms (Hermes, OpenClaw). Ideal for market research, social listening, and content automation.

Utilize the Scapy library in Python to perform deep packet inspection, crafting, sending, and sniffing of various network protocols (TCP, UDP, ICMP, DNS). This skill is essential for analyzing pcap files, implementing advanced security techniques like SYN scans, extracting protocol fields, and detecting network anomalies such as fragmentation or tunneling indicators. Ideal for security researchers, SOC analysts, and penetration testers.

This is an advanced, structured workflow designed to conduct deep, multi-source investigations. It synthesizes current public evidence with user-provided context to generate highly structured reports. The workflow explicitly differentiates between verifiable facts, user-supplied evidence, logical inferences, and actionable recommendations, making it ideal for complex comparative analysis or continuous monitoring tasks.

This guide details strategies for finding the full legal birth names of European actors, particularly those from French and Eastern European backgrounds. When English sources or IMDb only list stage names, this technique emphasizes using regional resources like French Wikipedia and specific cultural identifiers (e.g., "People's Artist" USSR) to perform deep, targeted searches, ensuring the retrieval of accurate birth details.