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Found 328 Skills
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.
Implement and extend PostHog Data warehouse import sources. Use when adding a new source under posthog/temporal/data_imports/sources, adding datasets/endpoints to an existing source, or adding incremental sync support, pagination, credentials validation, and source tests.
Use when cognee is a Python AI memory engine that transforms documents into knowledge graphs with vector and graph storage for semantic search and reasoning. Use this skill when writing code that calls cognee's Python API (add, cognify, search, memify, config, datasets, prune, session) or integrating cognee-mcp. Covers the full public API, SearchType modes, DataPoint custom models, pipeline tasks, and configuration for LLM/embedding/vector/graph providers. Do NOT use for general knowledge graph theory or unrelated Python libraries.
Use SqlClient for raw SQL against mapped dataset aliases and parse columnar SQL responses safely.
Work with raster and imagery data including ImageryLayer, ImageryTileLayer, multidimensional data, pixel filtering, and raster analysis. Use for satellite imagery, elevation data, and scientific raster datasets.
Implement Syncfusion WPF TreeMap (SfTreeMap) control for hierarchical data visualization using nested rectangles. Use this when visualizing large datasets with hierarchical structure, creating heat maps, or displaying proportional data. This skill covers TreeMap configuration, layout algorithms, color mapping, data binding, and interactive features for stock analysis, data categorization, and hierarchical visualization scenarios.
Exploratory Data Analysis skill for CSV and parquet datasets with deterministic profiling, drift/anomaly scans, contract generation and validation, and optional memory writeback into skill-system-memory. The implementation is Polars-first (lazy scan for large files and early `--sample` head), includes high-cardinality guards for profile/importance/contract flows, and supports categorical correlation with Cramer's V. Use when building or reviewing tabular fraud/risk/data-quality workflows, profiling new datasets, checking leakage or drift, or saving/validating data contracts.
Generates a Jupyter notebook that evaluates a fine-tuned SageMaker model using LLM-as-a-Judge. Use when the user says "evaluate my model", "how did my model perform", "compare models", or after a training job completes. Supports built-in and custom evaluation metrics, evaluation dataset setup, and judge model selection.
Generates a Jupyter notebook that transforms datasets between ML schemas for model training or evaluation. Use when the user says "transform", "convert", "reformat", "change the format", or when a dataset's schema needs to change to match the target format — always use this skill for format changes rather than writing inline transformation code. Supports OpenAI chat, SageMaker SFT/DPO/RLVR, HuggingFace preference, Bedrock Nova, VERL, and custom JSONL formats from local files or S3.
Use when the user needs ML pipelines, statistical analysis, data preprocessing, feature engineering, model selection, experiment tracking, or data visualization. Triggers: dataset exploration, model training, feature engineering, hyperparameter tuning, experiment tracking setup, statistical hypothesis testing, visualization creation.
Tableau platform help — Tableau Desktop, Tableau Cloud, Tableau Server, Tableau Prep, Tableau Pulse, Embedding API, REST API (v3.28, PAT/JWT auth, 300+ endpoints), MCP server, and Tableau+. Use when dashboards are slow with large datasets, LOD expressions or calculated fields aren't working, licensing costs are confusing or spiraling, Tableau won't connect to Salesforce or your data warehouse, embedded analytics aren't rendering, Tableau Prep flows keep failing, or you need help choosing Creator vs Explorer vs Viewer licenses. Do NOT use for general CRM config (use /sales-salesforce) or sales forecasting methodology (use /sales-forecast).
Implement Syncfusion React HeatMap Chart component for data visualization. Use this skill when user needs to create heatmaps, visualize 2D data patterns, display matrix data with color gradients, configure axes (numerical/categorical/datetime), implement legends, handle cell selection, apply custom styling, or work with large datasets. Covers installation, data binding, axis configuration, appearance customization, interaction patterns, tooltips, events, and accessibility.