Skill UI

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.

Research recent discussions on any topic by pulling posts and engagement from Reddit, X, YouTube, TikTok, Hacker News, Polymarket, GitHub, and the web. Includes source health checks to diagnose broken or missing data sources. Supports multi-platform social media analysis with citations.

Detects real-time significant price movements and unusual volume spikes across cryptocurrency markets. It calculates a composite significance score by combining price change, volume ratio, and market cap. Use it to track top gainers, biggest losers, or identify sudden market pumps across thousands of assets, with filtering options for category and timeframe.

Automates Snowflake data warehouse workflows via the Composio MCP, letting you list databases, schemas, and tables, run SQL (SELECT, DDL, DML), and integrate those operations into cross-app pipelines for faster data ops.

Provides programmatic access to the CZ CELLxGENE Census (61M+ cells) for querying standardized single-cell expression, metadata, embeddings, and stats across tissues and diseases, supporting scanpy and ML workflows.

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.

Use UMAP for fast nonlinear manifold reduction to produce embeddings that keep local and global structure, making it ideal for visualization, clustering preprocessing, supervised/parametric workflows, or high-dimensional feature engineering.

Umap provides uniform manifold approximation for dimension reduction and visualization, helping data scientists explore high-dimensional embeddings through interpretable 2D/3D layouts.

Perform comprehensive digital forensic analysis on raw (dd), E01, or AFF disk images using industry-standard tools like Autopsy and The Sleuth Kit. This process allows investigators to recover deleted files, examine file system metadata, search for specific keywords, and build detailed investigation timelines. It is essential for generating structured reports from digital evidence in legal and cybersecurity investigations.

This skill analyzes Indicators of Compromise (IOCs)—such as IP addresses, domains, and file hashes—by querying multiple threat intelligence platforms (VirusTotal, AbuseIPDB, MISP). It determines maliciousness confidence, assigns blocking priorities, and attributes threats to campaigns, crucial for incident response, threat triage, and making informed security decisions.

This tool correlates multiple system artifacts, including Windows registry keys (USBSTOR, MountedDevices), Event Logs, and SetupAPI logs, to reconstruct a detailed timeline of USB device usage. It determines first/last connection timestamps, tracks device provenance, and maps drive letter assignments. Essential for digital forensics investigations, insider threat detection, and verifying compliance regarding removable media usage.

A comprehensive toolset for digital forensics, designed to detect, extract, and analyze covert data hidden within images, audio, and video files. It utilizes advanced steganalysis techniques (LSB, DCT, frequency domain analysis) and specialized tools (StegDetect, zsteg, binwalk) to uncover hidden communications channels, making it crucial for investigations involving data exfiltration or insider threats.