Skill UI

This comprehensive skill provides systematic tools for academic research and writing. Users can search major databases (Google Scholar, PubMed), extract accurate metadata from identifiers (DOI, PMID, arXiv), validate existing citations, and generate correctly formatted BibTeX entries. It ensures reproducible research and maintains high citation accuracy throughout the writing process.

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 utility packages multiple independent FHIR R4 resources into a single, valid Transaction Bundle. It automatically handles deterministic URN UUID generation and resolves internal cross-references, making the bundle immediately ready for POSTing to a FHIR server. This is crucial for maintaining data integrity and interoperability when submitting multiple related clinical resources.

This skill provides an end-to-end workflow for creating a complete, local multimedia webpage project. Users only need to define the topic, target audience, visual style, and media preferences. The system automates the entire process, including requirement framing, content research, media acquisition (images, audio, video), code generation, project packaging, validation, and delivering comprehensive usage guides.

This is the master workflow for complex security competitions, including CTF, reverse engineering, cloud, pwnable, and forensics. It establishes a controlled sandbox model, treating user-presented targets as internal fixtures by default. The orchestrator's role is to map the entry surface, prove one minimal end-to-end path, and intelligently route the investigation to the most relevant specialized analysis skill or reference material.

This expert, interactive assistant provides comprehensive troubleshooting for complex issues encountered with Claude Code. It systematically scans the user's environment, checks global and project configurations, and cross-references symptoms against a deep knowledge base to pinpoint root causes and provide actionable, step-by-step solutions. Ideal for resolving integration errors, permission issues, or unexpected behavior.

This skill automatically detects and extracts tabular laboratory panels from diverse sources, including scanned images, photos, and delimited files (CSV/TSV). It converts complex visual data into clean, structured rows, capturing the test name, measured value, unit, reference range, and abnormal flag. It is essential for preparing medical data for subsequent standardization using LOINC and UCUM, and for mapping into FHIR resources.

This tool provides a comprehensive and safe mechanism to remove a git worktree. It includes multiple safety checks, such as verifying if the branch is protected, checking for uncommitted changes, and confirming merge status. Furthermore, it guides the user through the entire cleanup process, including deleting local and remote branches, pruning references, and reminding about associated database cleanup.

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.

This skill processes clinical text to interpret laboratory results. It parses reference ranges (e.g., "135-145", "<5") and derives structured abnormal flags (low, normal, high, critical) for a given numeric value. It is unit-agnostic and respects explicit flags provided by the originating lab, making it crucial for structured clinical data extraction and interpretation workflows.

A comprehensive guide for embedding OpenMed-powered tools into Electronic Health Records (EHRs) like Epic or Cerner. It covers the entire SMART on FHIR workflow, including OAuth2 PKCE authorization, granular scoping (e.g., patient/DocumentReference.rs), secure token handling, and processing clinical notes locally on-device for de-identification and Named Entity Recognition (NER).

This skill compiles comprehensive revision sheets from multiple inputs (pitch, slides, concepts). It structures the talk material into an actionable document containing quick navigation, a master concept table with URLs, a Q&A cheat-sheet, a glossary, and external resources list. Ideal for speakers who need to prepare for Q&A sessions or create shareable post-talk reference materials.