Skill UI

This skill integrates with DeepAPI to facilitate advanced web scraping, market research, and controlled email workflows. It handles scraping data from various sources like websites, LinkedIn, GitHub, and Twitter, while managing costs and ensuring explicit user approval for sensitive actions like sending emails. Use it for robust data extraction and automated reporting.

This skill provides comprehensive web browser automation capabilities for agents. It utilizes AI-optimized snapshots, reducing context size by 93% by using element references instead of full DOM. Functions include navigation, interactive element extraction, form filling, data scraping, and state management across multiple isolated sessions. Ideal for complex web testing and data extraction workflows.

This skill allows users to extract structured data (text, tables, attributes) from rendered web pages. It enhances traditional web scraping by ensuring all extracted strings pass mandatory AIDefence PII checks and prompt-injection gates before being stored or returned to the model. It supports building reusable extraction templates and running one-shot queries.

This skill analyzes completed code sessions to automatically extract reusable patterns, transforming raw interaction data into structured, learned skills. It allows the AI to continuously improve its domain knowledge by capturing techniques like error resolution, debugging methods, and workarounds, making it effective for advanced coding assistance and knowledge curation.

Use this skill for optimizing large-scale data ingestion, ETL, and data warehouse loading. It helps diagnose bottlenecks (such as extraction speed, network transfer, or loading time) and implements best practices like idempotent writes, native cloud scans, and checkpointing to achieve maximum processing speed while strictly guaranteeing data integrity and traceability.

This comprehensive API provides a robust solution for automated document workflows. Users can perform format conversions (PDF, DOCX, XLSX, etc.), extract structured data (text, tables), perform OCR on scanned documents, redact sensitive information (PII), add watermarks, and apply digital signatures. Suitable for building automated, secure document processing pipelines.

This skill automatically converts structured data from Excel (.xlsx) workbooks into a clean, readable Markdown format. It is essential for enabling accurate analysis, summarization, and data extraction of spreadsheet contents, especially when the user asks to 'read', 'analyze', or 'compare' data without specifying a conversion method. It supports both single files and batch processing of entire folders.

This comprehensive guide details the rigorous methodology for conducting systematic literature reviews and meta-analyses, particularly in educational research. It ensures the reproducibility and defensibility of the evidence corpus by documenting the entire PRISMA flow, from exhaustive multi-database searching and dual screening to structured data extraction and subsequent synthesis of findings.

Provides a comprehensive, step-by-step workflow for conducting rigorous literature reviews across academic, biomedical, and technical domains. It guides users through defining research questions (PICO), developing systematic search protocols, evidence logging, source screening, structured data extraction, and synthesizing findings to build high-quality, reproducible review reports.

This SDK allows asynchronous Python programming to control a live web browser, simulating user interactions for web automation, testing, and data extraction. Users can navigate pages, locate elements, fill forms, click buttons, and capture snapshots of the current page's content. It enforces a 'perceive → act → verify' cycle, making it ideal for building robust web scrapers and end-to-end testing tools.

A robust, on-device solution for processing large-scale clinical text corpora. Supports batch NER, PII extraction, and de-identification over thousands of notes. Features include sharding, checkpointing, resumable functionality, and streaming results to JSONL, ensuring PHI safety and constant memory usage for massive datasets.

This specialized downstream skill is designed for deep analysis of complex attack paths originating from Server-Side Request Forgery (SSRF). It systematically tracks the entire exploitation chain: from the initial SSRF source (e.g., webhook, URL parameter) through internal service reachability, metadata endpoint exploitation, credential extraction, and finally, demonstrating how an attacker achieves accepted access or elevated privileges. Use this when tracing the decisive path through server-side requests and credential pivoting.