Skill UI

Manage Zotero reference libraries programmatically with the pyzotero Python client and Zotero Web API v3. Retrieve, create, update and delete items, collections, tags and attachments; search libraries and export BibTeX or CSL-JSON citations for research automation workflows.

This skill provides comprehensive access to Bright Data's SERP API and Web Scraper API. It allows users to collect structured search engine results (Google, Bing, Yahoo) synchronously, or trigger large-scale, asynchronous data collections with webhooks. Ideal for market research, SEO analysis, and large-scale data scraping projects.

Executes the comprehensive workflow for claiming Research & Development (R&D) tax credits through Fondo. This skill guides users through qualifying R&D expense calculation, prepares the necessary Form 6765, and manages the payroll tax offset process for startups, potentially saving up to $500,000 annually.

This guide provides a comprehensive operational checklist for exploit development. It covers the entire lifecycle, from initial bug identification and vulnerability analysis (e.g., stack overflow, UAF) to payload development, mitigation bypass (ASLR, DEP, CFG), and reliable weaponization. Essential for security researchers developing Proof-of-Concept exploits and establishing a professional exploit development environment.

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.

This workflow utilizes the SerpApi to perform advanced, multi-engine searches across platforms including YouTube, Bing, Google News, Google Shopping, and Google Maps. It is essential for data scraping, SEO research, and building comprehensive search features that require aggregating results from diverse sources beyond standard Google search. Use it to collect videos metadata, product pricing, local business details, and news articles efficiently.

Analyzes Screenpipe history windows to detect repeated research workflows, match existing skills, and stage new skill drafts for review. Requires local Screenpipe daemon on localhost:3030 with optional LLM backend. Privacy-focused with data redaction before LLM processing. Use only when user explicitly requests workflow analysis.

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.

Orchestrates a 10-stage academic workflow from research to final manuscript, including integrity checks, two-stage peer review, revisions, and auditable quality assurance.

This comprehensive skill provides expert guidance for integrating with Google NotebookLM programmatically, covering both the `nlm` Command Line Interface (CLI) and Measurement/Control Plane (MCP) tools. Use it to automate workflows, manage notebooks, add diverse sources (URLs, YouTube, Drive), and generate various complex content types, such as reports, quizzes, mind maps, and videos. Essential for developers building upon NotebookLM's advanced research capabilities.

This meta-skill is designed for drafting and producing new academic or research papers and LaTeX manuscripts. It orchestrates a multi-step workflow, handling source search, citation planning, drafting, length checks, and final LaTeX/PDF compilation. It supports both compact outlines and full, publication-ready manuscripts.

This tool processes raw search results and bibliography entries to generate a highly structured and curated source pack for long-form academic papers. It categorizes sources into primary, supporting, and weak/excluded sources, ensuring the resulting literature review is reliable, diverse, and methodologically sound. Essential for academic writing workflows.