Web scraping is difficult and time-consuming. Crawl4AI provides 6 intelligent modes for extracting content, screenshots, and PDFs from any website with anti-detection features.

Alembic generates migrations without understanding PostgreSQL performance implications. This skill provides patterns for reviewing database migrations and writing efficient queries that avoid common performance pitfalls.

Building initial molecular structures for simulations requires precise spatial constraints. Packmol automates molecule placement with overlap prevention, supporting boxes, spheres, cylinders, and planes for diverse simulation needs.

Agents lose all knowledge when sessions end. This skill provides patterns for layered memory architectures that preserve entity knowledge, track relationships, and enable temporal queries across sessions.

Building reliable LLM evaluation systems is challenging due to systematic biases. This skill provides production-ready patterns for direct scoring, pairwise comparison, and bias mitigation to create trustworthy automated assessment pipelines.

Working with Excel files requires knowledge of formulas, formatting, and data analysis. This skill provides comprehensive guidance for creating spreadsheets, performing calculations, and analyzing data with professional standards.

Processing PDF documents manually takes too much time. This toolkit provides comprehensive PDF operations including text extraction, table detection, form filling, and document creation using Python and command-line tools.

Create original music compositions and convert MIDI files to MP3 or WAV audio files. Uses music21 library for intelligent composition and supports both orchestral and electronic music generation with realistic instrument sounds.

Users need expert guidance to understand Logseq's Datascript database architecture for effective knowledge graph management. This skill provides authoritative knowledge of schema design, property types, class hierarchies, and entity relationships.

Users need to extract and query data from their Logseq knowledge graphs. This skill provides a unified Python client library for fetching pages, blocks, properties, and executing advanced Datalog queries against local Logseq graphs via HTTP API or CLI.

Logseq users need clear guidance when transitioning from Markdown files to the Database format. This skill provides step-by-step migration planning, backup strategies, troubleshooting for common issues, and Datalog query examples for validation.

EDN template analysis is time-consuming when done manually. The edn-analyzer skill provides automated structure analysis, quality checks, and comparison features for Logseq database graph templates. It identifies orphaned items, validates structure, and generates actionable reports.

Users need to integrate Claude with their Logseq knowledge graphs for querying and writing data. This skill provides automated connection management across HTTP API, CLI, and MCP Server backends with built-in troubleshooting support.

Building phylogenetic trees from multiple genome assemblies requires complex workflows with many tools. This skill generates ready-to-run, scheduler-aware scripts for the complete BUSCO-based phylogenomics pipeline.

Phylogenetic biogeographic analysis helps researchers understand how species geographic ranges evolved over time. This skill automates the complete BioGeoBEARS workflow from input validation to publication-ready ancestral range visualizations.

Manually collecting YouTube channel and video data is slow and error-prone. This skill automates extraction of structured video metrics including views, likes, comments, subscriber counts, and posting schedules through a single API request.

YouTube videos contain valuable information but watching them takes significant time. This skill extracts full transcripts and metadata from any public YouTube video URL automatically using the BrowserAct API, giving you the content without the video.

Manually copying YouTube video and comment data is slow and error-prone. This skill automates extraction of structured video metadata and viewer comments using the BrowserAct API, giving you clean datasets from any search keyword.

Manually searching and recording YouTube channel information is slow and error-prone. This skill automatically extracts structured channel data including subscriber counts, handles, and descriptions from YouTube search results using the BrowserAct API.

Manually collecting YouTube transcripts and metadata is slow and repetitive. This skill automates batch extraction via the BrowserAct API, delivering structured subtitles, titles, and channel data with a single command.