Skill UI

A comprehensive skill for detecting and analyzing malicious behavior in mobile applications (Android/iOS). It employs multi-layered security analysis, including static indicator checking (permissions, manifest), dynamic instrumentation (Frida), network traffic monitoring, and automated scanning (MobSF). Use this skill when investigating suspicious apps for data exfiltration, C2 communication, or unauthorized access.

A specialized tool for scientific data visualization, acting as a visualization advisor to analyze data, recommend chart types, prevent common errors, and generate publication-grade figures.

Generates sophisticated, editorial-grade data visualizations inspired by major news publications like The New York Times. Ideal for presenting complex data (CSV/JSON) or key conclusions as single frames or animations for video explainers, social media posts, or data reports. Features clean design, specific typography, and staggered reveal animations.

Build a production-ready, AI-powered data collection agent for any public source (job boards, prices, news, etc.). This agent automatically scrapes data, enriches it using free LLMs (like Gemini Flash), and stores the results in databases such as Notion, Sheets, or Supabase. It runs on a free schedule using GitHub Actions and learns from user feedback, making it ideal for continuous data monitoring and tracking.

This skill guides the process of converting complex, repetitive, and often private operational workflows originating in the Hermes environment into safe, reusable, and public skills for the ECC workflow layer. It focuses heavily on data sanitization, requiring users to strip out all sensitive information such as absolute paths, private credentials, personal identifiers, and proprietary data before publication. Use this when an internal 'operator' routine needs to become a standardized, shareable business asset.

This guide provides a comprehensive workflow for searching and retrieving biomedical literature from PubMed and NCBI. It covers advanced query construction using MeSH terms and specific field tags, advanced filtering (date, publication type), and a repeatable programmatic workflow using NCBI E-utilities (esearch, efetch). Essential for researchers conducting systematic reviews and literature monitoring.

A comprehensive set of guidelines for generating maps, figures, and tables for academic journals. This guide emphasizes cartographic standards, statistical rigor, and maximizing the visual argument, ensuring that all exhibits are reproducible, legible in print, and adhere to strict word count limitations. It covers everything from projection choice and data normalization to model plot interpretation and handling spatial uncertainty.

A comprehensive guide for authors transitioning an accepted, anonymous conference submission into the final, public camera-ready version for publication. It covers de-anonymization steps, including restoring author details, updating proceedings metadata, reflowing figures for multiagent papers, and integrating rebuttal promises without expanding the core contribution. This ensures adherence to strict publishing standards.

Provides comprehensive guidelines on structuring academic manuscripts for Acta Automatica Sinica (AAS). Learn how to effectively separate core contributions (main text) from supporting details, such as lengthy proofs, supplementary simulations, and extensive datasets, ensuring the paper remains concise and highly readable while maintaining scientific completeness for reviewers.

A comprehensive guide for packaging and submitting evidence packages (artifacts) for NLP research papers, such as code, datasets, prompts, and model outputs. It details requirements for reproducibility, adhering to the Responsible NLP checklist, ensuring proper anonymization, and preparing for post-acceptance public release in academic settings like ACL.

This comprehensive guide outlines the meticulous workflow for preparing a research paper for final publication (Camera-Ready) after acceptance at major NLP conferences like ACL. It covers critical steps including de-anonymization (restoring author details and acknowledgements), integrating mandates from meta-reviews, adding required disclosures (e.g., funding, AI assistance), and ensuring all technical metadata, font embedding, and licensing comply with the permanent open-access standards of the ACL Anthology.

A comprehensive guide for structuring research artifacts (code, models, datasets, media) for ACM Multimedia conferences. It details the distinct requirements for anonymous review packages versus permanent public releases, offering guidelines on ethics, licensing, reproducibility, and track-specific documentation.