Skill UI

This comprehensive reference architecture details a multi-stage pipeline for web scraping and content ingestion using Firecrawl. It seamlessly integrates single-page scraping, site-wide crawling, URL mapping, and structured data extraction. The subsequent processing layer handles cleaning, deduplication, and chunking, making this blueprint ideal for designing robust knowledge bases, RAG systems, and complex AI data pipelines.

Access the BRENDA SOAP API to retrieve enzyme kinetic parameters, reaction equations, organism-specific data, and environmental preferences, enabling biochemical research, metabolic pathway reconstruction, and enzyme engineering workflows.

This reference architecture provides a comprehensive blueprint for building a robust revenue intelligence data platform integrated with Clari. It covers the entire data lifecycle, including API data extraction (ETL pipeline), data warehousing design (Snowflake/BQ), change detection logic, and advanced analytics/alerting layers. Use this guide when designing a scalable forecast tracking system, planning complex data integrations, or establishing best practices for enterprise revenue analytics.

This guide provides a comprehensive reference architecture for building production-ready, enterprise-grade applications on Palantir Foundry. It covers the entire data lifecycle, detailing best practices for the standard data pipeline (Raw > Clean > Model), Ontology design, external API integration patterns, and robust multi-layered security models. Use it when designing, planning, or optimizing complex data infrastructure within Foundry.

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 skill provides a comprehensive guide for authors targeting top-tier Chinese academic journals, such as the Chinese Review of Financial Studies. It analyzes the journal's specific academic scope (finance theory, capital markets, etc.), required manuscript structure, submission formatting (abstract length, JEL codes, reference rules), and common pitfalls. Use it pre-submission to ensure your paper meets the high academic standards required for CSSCI-level publication.

gget is a versatile CLI and Python package designed for rapid, reproducible bioinformatics searches across major genomic reference databases (e.g., Ensembl, UniProt). It allows users to quickly query gene metadata, perform initial BLAST/BLAT style alignments, and explore associated pathways, cancer, or disease modules. It is ideal for initial data exploration and generating reproducible evidence logs before building complex, full-scale local pipelines.

This skill implements an advanced reference pattern for integrating with Monitoring Control Platform (MCP) servers. It ensures accurate data retrieval by first reading a domain-specific 'gotchas' reference file, mitigating query failures caused by complex server behaviors, pagination limits, or subtle API quirks. It analyzes issue data, groups errors by root cause, and generates a structured, actionable markdown report for improved system health visibility.

Query the FXMacroData REST API for official macro indicators, release calendars, central-bank policy rates, daily FX reference rates and CFTC positioning across 22 currencies, with publisher citations and release timestamps.