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Found 331 Skills
Digital pathology image processing toolkit for whole slide images (WSI). Use this skill when working with histopathology slides, processing H&E or IHC stained tissue images, extracting tiles from gigapixel pathology images, detecting tissue regions, segmenting tissue masks, or preparing datasets for computational pathology deep learning pipelines. Applies to WSI formats (SVS, TIFF, NDPI), tile-based analysis, and histological image preprocessing workflows.
Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.
Create production-quality data visualizations including charts, dashboards, and infographics. Use when the user asks to visualize data, create charts, build dashboards, make infographics, plot statistics, or transform datasets into visual representations. Supports React/Recharts artifacts, static images (PNG/PDF via Python), and interactive HTML. Triggers include "visualize this data", "create a chart", "build a dashboard", "make a graph", "plot this", "infographic", or any request to represent data visually.
Expert ReactFlow architect for building interactive graph applications with hierarchical node-edge systems, performance optimization, and auto-layout integration. Use when Claude needs to create or optimize ReactFlow applications for: (1) Interactive process graphs with expand/collapse navigation, (2) Hierarchical tree structures with drag & drop, (3) Performance-optimized large datasets with incremental rendering, (4) Auto-layout integration with Dagre, (5) Complex state management for nodes and edges, or any advanced ReactFlow visualization requirements.
Integrate and analyze multiple omics datasets (transcriptomics, proteomics, epigenomics, genomics, metabolomics) for systems biology and precision medicine. Performs cross-omics correlation, multi-omics clustering (MOFA+, NMF), pathway-level integration, and sample matching. Coordinates ToolUniverse skills for expression data (RNA-seq), epigenomics (methylation, ChIP-seq), variants (SNVs, CNVs), protein interactions, and pathway enrichment. Use when analyzing multi-omics datasets, performing integrative analysis, discovering multi-omics biomarkers, studying disease mechanisms across molecular layers, or conducting systems biology research that requires coordinated analysis of transcriptome, genome, epigenome, proteome, and metabolome data.
Comprehensive skill for Microsoft GraphRAG - modular graph-based RAG system for reasoning over private datasets
Dune CLI for querying blockchain and on-chain data via DuneSQL, searching decoded contract tables, managing saved queries, and monitoring credit usage on Dune Analytics. Use when user asks about blockchain data, on-chain analytics, token transfers, DEX trades, smart contract events, wallet balances, Ethereum/EVM chain queries, DuneSQL, or says "query Dune", "search Dune datasets", or "run a Dune query".
Use this skill when the user wants to debug, diagnose, or systematically iterate on an experiment that already exists, or when they need a structured experiment log for tracking runs, hypotheses, failures, results, and next steps during active research. Apply it to underperforming methods, training that will not converge, regressions after a change, inconsistent results across datasets, aimless experimentation without progress, and questions like 'why doesn't this work?', 'no progress after many attempts', or 'how should I investigate this failure?'. Also use it for setting up practical experiment logging/record-keeping that supports debugging and iteration. Do not use it for designing a brand-new experiment pipeline or full experiment program (use experiment-pipeline), generating research ideas, fixing isolated coding/syntax errors, or writing retrospective summaries into research memory/notes/knowledge bases.
Generate deep links to the Arize UI. Use when the user wants a clickable URL to open a specific trace, span, session, dataset, labeling queue, evaluator, or annotation config.
Prepare datasets and configure LoRA training for character consistency. Covers FLUX (AI-Toolkit, SimpleTuner, FluxGym) and SDXL (Kohya_ss) training with step-by-step guidance. Use when training custom character LoRAs.
Automates declarative resource creation and provisioning for data pipelines, supporting BigQuery, Dataform, Dataproc, BigQuery Data Transfer Service (DTS), and other resources. It manages environment-specific configurations (dev, staging, prod) through a deployment.yaml file. Use when: - Modifying or creating deployment.yaml for deployment settings. - Resolving environment-specific variables (e.g., Project IDs, Regions) for deployment. - Provisioning supported infrastructure like BigQuery datasets/tables, Dataform resources, or DTS resources via deployment.yaml. Do not use when: - Resources already exist. - Managing resources not supported by `gcloud beta orchestration-pipelines resource-types list`. - Managing general cloud infrastructure (VMs, networks, Kubernetes, IAM policies), which are better suited for Terraform. - Infrastructure spans multiple cloud providers (AWS, Azure, etc.). - Already uses Terraform for the target resources.
Resolve data lake and lakehouse asset references across Glue Data Catalog, S3, S3 Tables, and Redshift. Triggers on: find the table, where is our data, which table has, locate dataset, find data for, search catalog, what tables match, Redshift table, lakehouse table, data lake table, warehouse table, reverse lookup S3 path. Do NOT use for: full catalog audits (use exploring-data-catalog), running queries (use querying-data-lake), creating tables (use creating-data-lake-table).