Skill UI

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 toolkit designed to track and analyze content performance, engagement metrics, and Return on Investment (ROI) across major social media platforms. By utilizing specialized Apify Actors, this skill extracts deep insights from Instagram, Facebook, YouTube, TikTok, and more, helping users identify high-performing content, monitor growth, and measure marketing campaign effectiveness.

Literature Review Tool helps researchers gather and synthesize key insights from scholarly texts, highlighting patterns and critical arguments to accelerate literature surveying workflows even when structured content is initially unavailable.

This skill guides the creation of high-quality, finished cyber threat intelligence reports. It tails content for specific audiences—from C-suite executives (strategic risk) to SOC analysts (tactical IOCs). Use it when synthesizing raw data into actionable intelligence products, generating threat briefings, or conducting post-incident assessments, ensuring adherence to industry standards like TLP and NIST.

This internal agent skill processes raw X/Twitter posts into structured bug candidates. It systematically performs parsing, content deduplication, PII redaction, reliability scoring, and classification. Finally, it clusters related reports using deterministic signatures, providing a highly organized output for efficient bug triage and analysis from large-scale social media streams.

This skill scrapes Substack Notes analytics by extracting key engagement metrics (likes, comments, restacks) and content details. It overcomes the lack of a public API, allowing users to analyze performance data from a specified date range into a highly formatted, actionable Excel spreadsheet. The output includes detailed per-note data, total engagement calculations, and summary statistics.

This skill adapts scholarly drafts to the specific, rigorous style of the Journal of Financial and Quantitative Analysis (JFQA). It enforces quantitative prose, strict formatting (e.g., 100-word abstract, TNR 12pt, double-spacing), and structural rules necessary for high-impact finance submissions. Use it to polish content, ensure precision, and guarantee compliance with top academic journal standards.

A comprehensive style guide for revising research papers to meet the specific, high standards of KDD conferences. It details the expected structure of the first page, emphasizing data regimes, named mechanisms, and quantifiable evidence (scale, metrics). It also provides rules for differentiating research vs. applied data science (ADS) voices and optimizing content for two-column, page-limited formats.

This guide provides comprehensive standards for formatting tables and figures for high-level academic journals. It details rigorous requirements, such as adhering to the three-line table format (booktabs), limiting columns, correctly placing standard errors, and ensuring figures meet minimum DPI and color constraints. Use this when transforming raw statistical outputs into publication-ready, professional content.