Search Skills

Adds Railway database services (Postgres, Redis, MySQL, MongoDB) via natural language commands for seamless infrastructure integration.

Guides training and analysis of Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features for model analysis.

Accelerates transformer training/inference with 2-4x speedup and 10-20x memory reduction using Flash Attention for long sequences.

Implements infrastructure as code with Terraform and Kubernetes, designing scalable architectures, CI/CD pipelines, and security-first DevOps solutions for cloud platforms.

Provides tools for building and training Graph Neural Networks (GNNs) for node classification, link prediction, and molecular property prediction using PyTorch Geometric.

Automates fixing and pushing code to a pull request until all CI checks pass, eliminating manual iteration cycles.

Python library for quantum machine learning, quantum circuit design, and hybrid quantum-classical model training with automatic differentiation and PyTorch integration.

Predicts protein-ligand binding poses and confidence scores using diffusion models, supporting PDB and SMILES inputs for structure-based drug design.

Provides zero-shot image segmentation using points, boxes, or masks as prompts, or automatically generates all object masks in an image.

Automates exploratory data analysis for scientific datasets, detecting file types and generating structured reports with quality metrics and recommendations.

Provides access to and analysis of comprehensive drug data from DrugBank, including properties, interactions, targets, and pharmacology for research and discovery.

Enables machine learning analysis of genomic regions using BED files, including region embeddings and scATAC-seq processing.

Accesses ZINC database for drug discovery, enabling compound searches by ID, SMILES, similarity, and 3D structure analysis for virtual screening.

Enables constraint-based metabolic modeling with FBA, FVA, gene knockouts, and SBML support for systems biology and metabolic engineering analysis.

Plans, creates, and optimizes marketing campaigns with content strategy, social media, email, and analytics for effective go-to-market execution.

Provides advanced prompt engineering for LLM optimization, RAG, agent design, and structured outputs to enhance AI product performance.

Efficiently search bioRxiv preprints by keywords, authors, or date ranges, retrieving metadata and PDFs for scientific literature reviews.

Systematically diagnoses and resolves software errors using first-principle analysis, supporting replay of solutions for future reference.

Creates and edits visual diagrams (mind maps, flowcharts) using Obsidian's .canvas file format.

Provides direct REST API access for protein data retrieval from UniProt, including searches, FASTA sequences, and ID mapping for bioinformatics workflows.

Provides no-code web interface for fine-tuning large language models with quantization support and multimodal capabilities.

Provides API integration for electronic lab notebooks (ELN) to manage entries, attachments, and workflows with scientific tools including Jupyter and REDCap.

Evaluates research rigor, methodology, statistical validity, and evidence quality using frameworks like GRADE and Cochrane ROB for scientific claim analysis.

Provides a process-based discrete-event simulation framework for modeling systems with queues, resources, and time-based events in Python.