Skill UI

A comprehensive, structured framework for conducting sophisticated Open Source Intelligence (OSINT) and cryptocurrency forensic investigations. This guide covers operational security (OpSec), target profiling, advanced transaction tracing across multiple blockchain layers (L1/L2), wallet analysis, and identifying linked digital assets. Use this methodology to guide systematic, multi-dimensional intelligence collection campaigns.

This advanced skill is an end-to-end tool for transforming complex research topics into professional, visualized knowledge graph PDFs. It automatically conducts multi-round web searches, extracts key entities, structures related knowledge, and designs the optimal visualization (supporting Graphviz, PlantUML, etc.). Ideal for deep academic analysis, mapping character relationships, or visualizing complex technical architectures where existing structured data is unavailable.

A comprehensive workflow for scraping and extracting structured data from Google search results using the SerpApi. It captures all key components, including organic listings, knowledge graphs, answer boxes, People Also Ask (PAA), local pack results, and related searches. Ideal for SEO monitoring, market research, competitive analysis, or building search-powered features that require deep, structured data insights.

Provides a structured workflow for systematically accessing and analyzing official intellectual property data from the USPTO. This skill covers patent search (PatentSearch API), trademark status checks (TSDR), ownership transfer tracking, and building reproducible IP landscape logs. It is designed for data collection and record verification, emphasizing the use of official APIs and rigorous logging practices. (Warning: Not for legal advice.)

This engine aggregates news from multiple RSS sources (e.g., TechCrunch, The Verge) and performs advanced sentiment analysis using AI (Claude). It ranks articles by industry impact, generates structured summaries, and provides actionable commentary, making it ideal for daily tech/AI briefing preparation and market monitoring.

A comprehensive, domain-agnostic 13-agent system designed for rigorous academic research on any topic. It guides users through the entire research lifecycle, supporting deep literature reviews, systematic meta-analysis, cross-source synthesis, bias assessment, and generating professional APA 7.0 reports. Ideal for academics, students, and analysts needing structured, deep insights.

A comprehensive tool for extracting YouTube transcripts, searching videos, browsing channels, and monitoring new uploads. It supports detailed transcript analysis, content summarization, and playlist management by leveraging the TranscriptAPI. Ideal for researchers, content strategists, and market analysts who need structured data from video content without downloading files.

This meta-skill is designed for complex decision analysis when a user provides or references structured documents such as contracts, quotes, spreadsheets, or notices. Instead of simple summarization, it extracts key evidence, identifies risks (e.g., renewal risk, payment terms), and structures the output into decision-ready formats, such as 'sign/reject/negotiate' recommendations, evidence tables, or required next actions. It supports input from PDF, DOCX, and XLSX formats.

This meta-skill orchestrates a comprehensive workflow for analyzing PDF documents. It handles complex tasks such as summarizing, cross-document comparison, and targeted Q&A. It ensures findings are traceable by indexing evidence from various sources (full PDFs, pasted excerpts, etc.) and synthesizing structured insights across multiple files.

This meta-skill processes an entire Excel workbook to extract deep business insights. It systematically reads all data, performs structured trend and anomaly analysis, writes the comprehensive results back into a dedicated 'Insights' sheet, and permanently stores key performance indicators (KPIs) in long-term memory. Ideal for detailed business review and data deep-dives.

This skill processes raw, unstructured materials (e.g., conversations, reports, controversies) into highly structured, reusable casebook entries. It focuses on identifying core facts, defining mechanism chains, and mapping responsibility links while ensuring rigorous data anonymization. It is designed for deep knowledge management and pattern recognition, helping users build a reliable, reusable knowledge base for future professional analysis, rather than generating immediate advice.

This skill provides a highly rigorous framework for analyzing complex public issues, platform governance, and institutional compliance. It is designed to structure evidence boundaries, assess procedural justice, and track public commitments by synthesizing source ledgers and multiple data points. It is intended as a specialized sub-routine triggered by the main CrossFrame suite, not for standalone use. Key focus areas include source verification, identifying weak signals, and mitigating AI compliance performance risks.