Skill UI

A comprehensive skill for analyzing Non-Fungible Tokens (NFTs). It fetches collection metadata from APIs (like OpenSea), parses trait attributes, and calculates advanced rarity scores using multiple algorithms (e.g., rarity_score, information entropy). Use this tool to rank tokens by uniqueness, compare specific NFTs, or analyze the distribution of traits within an entire collection, outputting results in JSON or CSV format. Ideal for crypto research and market due diligence.

This skill provides comprehensive guidelines for monitoring Granola usage, tracking team meeting patterns, and building detailed analytics dashboards. It guides users in defining critical metrics (e.g., adoption rate, efficiency score) and establishing robust data pipelines. Users can stream meeting metadata from Granola to data warehouses like BigQuery, enabling deep, customizable reporting and automated weekly insights via services like Zapier and Slack.

Auto-activating skill guiding metadata extractor implementations within data pipelines, covering ETL, transformation, orchestration, and streaming best practices.

This skill provides comprehensive, structured audit logging for OpenRouter API interactions. It automatically captures essential metadata like total cost, token usage, model details, latency, and status, while also performing PII redaction. The resulting audit trail is stored in an append-only SQLite database, making it ideal for building compliance-ready systems, detailed cost monitoring, and deep debugging of production environments.

Use this skill to perform read-only API calls for exploring, previewing, searching, and filtering structured datasets hosted on Hugging Face. It allows users to validate dataset availability, list splits, paginate large datasets, and retrieve comprehensive metadata and statistics, making it ideal for data validation and content extraction workflows.

A specialized tool for searching published, peer-reviewed academic papers from major venues like IEEE, ACM, and Springer. Unlike preprint services (like arXiv), this skill provides verified citation counts, detailed venue metadata, and filtering options for finding established, high-impact research literature. Ideal for formal academic research and literature reviews.

This skill provides comprehensive commands to manage the entire AI model evaluation lifecycle using Arize. Users can list, retrieve metadata, and export results from experiments. It is ideal for comparing multiple model runs, benchmarking performance against a dataset, and analyzing model accuracy using structured evaluation workflows (CRUD operations).

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.

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.

This comprehensive guide covers essential operations for handling PDF documents, including text, table, and metadata extraction using libraries like pdfplumber. It details document creation with reportlab, merging/splitting with pypdf/qpdf, and advanced OCR for scanned PDFs. Ideal for automating complex document workflows and structured data ingestion.

This skill automatically processes MP4 videos by extracting key frames at configurable intervals. It then applies Tesseract OCR to recognize text on these frames, generating a comprehensive, structured Markdown report. The report includes full video metadata and timestamped, searchable transcripts, making it ideal for analyzing lectures, presentations, or screencasts programmatically.

This tool provides a read-only view over per-turn decision logs, aggregating data on skill co-occurrence patterns, meta-skill usage statistics, and router fixtures. It returns a structured JSON summary, making it ideal for analyzing historical skill usage, optimizing workflows, and feeding insights into downstream LLM models.