Skill UI

Search 18 scholarly APIs for papers, preprints, citations, open-access full text, repository records, and journal OA status with reproducible provenance.

This skill performs a structured Systematic Literature Review (SLR) by analyzing multiple academic papers on a given topic. It searches academic databases (like arXiv), extracts structured metadata (research questions, methodologies, key findings, limitations) from the entire set of papers, and synthesizes overarching themes and research trends. It is ideal for creating comprehensive literature surveys, annotated bibliographies, and cross-paper comparisons, outputting reports in professional citation formats like APA, IEEE, or BibTeX.

This skill leverages the Gemini AI model to perform comprehensive and broad literature discovery across academic domains. Unlike traditional APIs, it decomposes complex research queries into sub-problems, explores topic aliases, and surfaces highly relevant papers that might otherwise be missed. It is ideal for conducting deep, multi-angled literature reviews and achieving a holistic view of a research field.

A powerful skill for searching and retrieving comprehensive academic metadata using the OpenAlex API. It provides a unified view of research papers, including full open citation graphs, detailed institutional affiliations, and crucial funding information (e.g., NSF, NIH). Ideal for deep academic research, comparative literature reviews, and identifying research trends across multiple disciplines.

A universal deep research agent team with a 13-agent pipeline for rigorous academic research on any topic. Supports 8 modes including full research, quick brief, paper review, literature review, fact-check, three-way literature scan, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers question formulation, methodology design, systematic search, source verification, synthesis, bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research monitoring.

A comprehensive tool designed for academic literature orientation. It searches papers using free keyless APIs (PubMed and OpenAlex) and builds a structured 'launching pad' guide, rather than a finished review. It helps researchers define their scope using frameworks like PICO/SPIDER, ensuring a confident and systematic starting point for deep research in unfamiliar fields.

Bilig WorkPaper provides a code-first runtime environment for complex spreadsheet business logic. It allows agents to interact with structured data using formulas and JSON workbooks via deterministic API calls (MCP/TypeScript). This is ideal for replacing unreliable UI automation in use cases like quote calculators, budget modeling, and data validation, ensuring calculation integrity through explicit read-back proof.

This meta-skill fetches the top academic papers from the arXiv API in a specified category. It generates a structured digest for each paper, renders this digest into a professional PowerPoint (PPTX) presentation (one slide per paper), and finally saves the comprehensive digest to long-term memory for future reference. Designed for daily 'morning briefings' of academic research.

This tool reads a CSV containing three columns (x, y_baseline, y_ours). It uses matplotlib to generate a two-line plot visualizing the results and saves the final output as a PDF file. It is specifically designed for visualizing performance comparisons in scientific papers.

This utility reads structured JSON outputs from multi-search-engine APIs (e.g., Google Scholar, arXiv) provided via standard input. It converts these normalized records into a clean, minimal BibTeX format, suitable for academic papers. It intelligently preserves crucial metadata like DOI, authors, and years while automatically handling data sanitization, deduplication of DOIs, and protecting complex fields like corporate names.

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.

Runs a SHA-pinned integrity-forensics sweep on a paper (evidence ledger, auditor proposals, rules-only report), converting verdicts into typed policy gates (BLOCK/WARN/NO_NEW_BLOCKER) and an obligations ledger. Used for pre-submission integrity checks, peer-review forensics and resubmission pipelines.