Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
146 skills found
Comprehensive Python healthcare AI toolkit for clinical data processing, medical coding translation, and developing deep learning models like RETAIN and Transformers for EHR, physiological signals, and clinical prediction tasks.
Run, debug, and manage DBHub tests including unit, integration with Testcontainers, and database-specific suites. Perfect for verifying code changes and troubleshooting database connector issues.
An Obsidian vault curator for identifying stub notes, detecting duplicates, fixing outdated information, and improving documentation quality in both English and Korean.
Expert code review agent that performs systematic audits of git changes for SOLID violations, security vulnerabilities, performance regressions, and architectural smells.
Your AI chief of staff for startups. Includes 28 commands for idea validation, financial modeling, pitch decks, market research, and CEO operational frameworks from industry benchmarks.
PyTorch Lightning skill for scalable deep learning: automates model training, multi-GPU orchestration, data pipelines, and distributed training strategies like DDP, FSDP, and DeepSpeed.
Definition of Done (DoD) verification workflow that triggers automatically upon implementation completion to ensure quality, document evidence, and standardize reporting.
Generate publication-quality figures, charts, and LaTeX tables from experiment data for academic papers.
Run mutation testing to measure test suite effectiveness by introducing code faults and verifying test failure detection.
Verify research idea novelty against recent literature. Use when user says '查新', 'novelty check', or needs to confirm if a method is original.
Generate optimized SQL queries from natural language. Supports BigQuery, PostgreSQL, MySQL, and Snowflake. Analyze database schemas, interpret business requirements, and output ready-to-run queries with explanations.
Search codebases efficiently using ripgrep for lightning-fast text patterns and ast-grep for precise, syntax-aware structural code analysis.