data-science/
435 total · showing first 300jupyter-live-kernel
Iterative Python via live Jupyter kernel (hamelnb).
nemo-curator
GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic…
Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one…
Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form…
googlebigquery-automation
Automate Google BigQuery tasks via Rube MCP (Composio): run SQL queries, explore datasets and metadata, execute MBQL queries via Metabase integration. Always search tools first…
azure-ai-ml-py
Azure Machine Learning SDK v2 for Python. Use for ML workspaces, jobs, models, datasets, compute, and pipelines.
azure-storage-file-datalake-py
Azure Data Lake Storage Gen2 SDK for Python. Use for hierarchical file systems, big data analytics, and file/directory operations.
azure-monitor-query-py
Azure Monitor Query SDK for Python. Use for querying Log Analytics workspaces and Azure Monitor metrics.
llm-prompt-optimizer
Use when improving prompts for any LLM. Applies proven prompt engineering techniques to boost output quality, reduce hallucinations, and cut token usage.
local-llm-expert
Master local LLM inference, model selection, VRAM optimization, and local deployment using Ollama, llama.cpp, vLLM, and LM Studio. Expert in quantization formats (GGUF, EXL2) and…
python-pptx-generator
Generate complete Python scripts that build polished PowerPoint decks with python-pptx and real slide content.
spreadsheets
Create, edit, analyze, clean, or convert spreadsheets including XLSX, CSV, TSV, formulas, charts, and tabular reports.
uv-package-manager
Master the uv package manager for fast Python dependency management, virtual environments, and modern Python project workflows. Use when setting up Python projects, managing…
airflow-dag-patterns
Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling…
azure-pricing
Fetches real-time Azure retail pricing using the Azure Retail Prices API (prices.azure.com) and estimates Copilot Studio agent credit consumption. Use when the user asks about…
dataverse-python-advanced-patterns
Generate production code for Dataverse SDK using advanced patterns, error handling, and optimization techniques.
medchem
Medicinal chemistry filters for compound triage. Apply drug-likeness rules (Lipinski, Veber, CNS), structural alert catalogs (PAINS, NIBR, ChEMBL), complexity metrics, and the…
geopandas
Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric…
polars
High-performance DataFrame library for Python ETL, analytics, and pandas migration. Use for expression-based data manipulation with lazy query optimization, parallel execution…
scikit-learn
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality…
aeon
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity…
anndata
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for…
arboreto
Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell…
cellxgene-census
Query the CZ CELLxGENE Census programmatically for versioned public single-cell and spatial transcriptomics data. Use when you need population-scale cell metadata, gene…
dask
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file…
deepchem
Molecular ML with diverse featurizers and pre-built datasets. Use for property prediction (ADMET, toxicity) with traditional ML or GNNs when you want extensive featurization…
depmap
Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), drug sensitivity data, and gene effect profiles. Use for identifying…
geniml
This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell…
gtars
High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection…
molfeat
Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.
pathml
Full-featured computational pathology toolkit. Use for advanced WSI analysis including multiplexed immunofluorescence (CODEX, Vectra), nucleus segmentation, tissue graph…
seaborn
Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box…
shap
Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature…
statsmodels
Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for…
tiledbvcf
Efficient storage and retrieval of genomic variant data using TileDB. Scalable VCF/BCF ingestion, incremental sample addition, compressed storage, parallel queries, and export…
experimental-design
Design experiments and studies BEFORE data is collected — choosing a design, randomizing, blocking, and laying out treatment combinations so the results will actually be…
geomaster
Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite…
pennylane
Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing…
polars-bio
High-performance genomic interval operations and bioinformatics file I/O on Polars DataFrames. Overlap, nearest, merge, coverage, complement, subtract for BED/VCF/BAM/GFF…
statistical-analysis
Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use…
Read, extract (text/tables), create, merge/split/rotate, watermark, encrypt,
xlsx
Read, create, or edit Excel spreadsheets (.xlsx/.xlsm) — sheet data,
cli-creator
Build a composable CLI for Codex from API docs, an OpenAPI spec, existing curl examples, an SDK, a web app, an admin tool, or a local script. Use when the user wants Codex to…
cohort-analysis
Perform cohort analysis on user engagement data — retention curves, feature adoption trends, and segment-level insights. Use when analyzing user retention by cohort, studying…
candlestick
Candlestick pattern recognition engine, pure pandas vectorized implementation of 15 classic candlestick patterns (5 single-candle + 5 double-candle + 4 triple-candle + 1 trend…
chanlun
基于缠论（缠中说禅）的形态识别引擎，使用czsc库自动检测K线分型、笔、中枢，并生成一买/一卖/二买/二卖/三买/三卖等买卖点信号。支持多周期分析和形态分类（3/5/7/9/11笔形态）。
correlation-analysis
Correlation and cointegration analysis — co-movement discovery, deep return-correlation analysis, sector clustering, realized correlation, Engle-Granger / Johansen cointegration…
elliott-wave
Elliott Wave Theory signal engine. Detects swing points through Zigzag, matches 5-wave impulse and 3-wave corrective structures, validates them with Fibonacci wave relationships…
event-driven
Event-driven strategy based on sentiment-scored signals from news, announcements, and macro events. The LLM acts as the NLP engine, and event data follows a CSV schema.
ichimoku
Ichimoku Kinko Hyo five-line system signal engine. A standalone Japanese technical-analysis school that generates trading signals from Tenkan/Kijun crossovers, cloud position…
minute-analysis
Minute-level data analysis and backtesting. Retrieves minute candlesticks through OKX/Tushare/yfinance and can be used both for analysis and as input to the backtest engine.
ml-strategy
Machine-learning predictive strategy based on sklearn walk-forward training, feature engineering, and signal generation. Suitable for any OHLCV data.
multi-factor
Multi-factor cross-sectional stock ranking. Combines factor standardization, equal-weight or IC-weighted scoring, and TopN portfolio construction. Suitable for multi-instrument…
okx-market
OKX cryptocurrency market data interface. Uses the OKX V5 REST API to retrieve spot, derivatives, index, and other crypto market data, including real-time prices, candlesticks…
pair-trading
Pair trading strategy. Trades mean reversion using the spread/ratio Z-score of two correlated instruments. Requires at least two instruments.
risk-analysis
Risk measurement and stress testing — VaR/CVaR/max drawdown calculation, Monte Carlo simulation, extreme-value tail-risk analysis, and historical scenario stress testing.
smc
Smart Money Concepts (ICT) signal engine. Uses the smartmoneyconcepts library to implement institutional-trading-school analysis of BOS, ChoCH, FVG, and order blocks (OB).
technical-basic
Core technical indicator collection (trend EMA/ADX + mean-reversion BB/RSI + volume-price OBV/volume ratio), generates a composite signal via three-dimensional voting. Pure…
tushare
tushare是一个财经数据接口包，拥有丰富的数据内容，如股票、基金、期货、数字货币等行情数据，公司财务、基金经理等基本面数据。该模块通过标准化API方式统一了数据资产的对外服务方式，以帮助有需要的技术用户更实时、简洁、轻量的使用相关数据。
volatility
Volatility strategy. Trades mean reversion based on percentile ranking of historical volatility (HV). Suitable for any OHLCV data.
senior-data-scientist
World-class senior data scientist skill specialising in statistical modeling, experiment design, causal inference, and predictive analytics. Covers A/B testing (sample sizing…
statistical-analyst
Run hypothesis tests, analyze A/B experiment results, calculate sample sizes, and interpret statistical significance with effect sizes. Use when you need to validate whether…
strict-api
Use when the user says 'no hallucinations', 'verify APIs', 'reality check', or 'don't invent functions'. Prevents the agent from calling methods, imports, or variables that do…
universal-scraping-architect
Use for web scraping, crawling, document extraction, API parsing, or building validation-heavy data pipelines using Firecrawl or local Python scripts.
scrape
This skill searches job portals using the installed portal-search CLIs in
timescaledb
TimescaleDB - PostgreSQL extension for high-performance time-series and event data analytics, hypertables, continuous aggregates, compression, and real-time analytics
bigquery-ai-ml
This skill defines the usage and rules for BigQuery AI/ML functions,
data-analyst
Data analysis expert for statistics, visualization, pandas, and exploration
ml-engineer
Machine learning engineer expert for PyTorch, scikit-learn, model evaluation, and MLOps
bigquery-ai-ml
BigQuery integrates with Vertex AI to provide powerful machine learning and
agent-platform-eval-flywheel
Help users evaluate and iteratively improve GenAI models and agents using
agent-platform-model-registry
This skill provides instructions for managing machine learning models in the
bigquery-basics
BigQuery is a serverless, AI-ready data platform that enables high-speed
bigquery-bigframes
Avoid .topandas(): You MUST NOT use .topandas() to download the
google-cloud-solution-agentic-ai-data-science-workflow
This skill guides agents through the workflow to design and implement a
golden-jupyter
Use when testing the golden_jupyter golden build
golden-jupyter-dir
Use when testing the golden_jupyter_dir golden build
golden-jupyter-kw
Use when testing the golden_jupyter_kw golden build
golden-jupyter-topics
Use when testing the golden_jupyter_topics golden build
fba-simulator
The fba-simulator skill executes constraint-based metabolic simulations on
flux-analyzer
The flux-analyzer skill transforms raw FBA output into actionable biological
quantum-qiskit
Reference qiskit 2.x patterns for variational quantum machine learning. Covers data-encoding feature maps, variational quantum classifier (VQC) training, variational quantum…
auto-review-loop-minimax
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with \"auto review loop…
maf-online-endpoint
Deploy a Microsoft Agent Framework (MAF) workflow as a managed online endpoint to an Azure ML workspace or an Azure AI Foundry hub-based project. Wraps any workflow into an…
transformers-js
Use Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript. Supports NLP (text classification, translation, summarization), computer…
evaluating-code-models
Evaluates code generation models across HumanEval, MBPP, MultiPL-E, and 15+ benchmarks with pass@k metrics. Use when benchmarking code models, comparing coding abilities, testing…
creative-thinking-for-research
Applies cognitive science frameworks for creative thinking to CS and AI research ideation. Use when seeking genuinely novel research directions by leveraging combinatorial…
langsmith-observability
LLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems…
prompt-guard
Meta's 86M prompt injection and jailbreak detector. Filters malicious prompts and third-party data for LLM apps. 99%+ TPR, <1% FPR. Fast (<2ms GPU). Multilingual (8 languages).…
ray-data
Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from…
ray-train
Distributed training orchestration across clusters. Scales PyTorch/TensorFlow/HuggingFace from laptop to 1000s of nodes. Built-in hyperparameter tuning with Ray Tune, fault…
sentence-transformers
Framework for state-of-the-art sentence, text, and image embeddings. Provides 5000+ pre-trained models for semantic similarity, clustering, and retrieval. Supports multilingual…
ml-pipeline
Designs and implements production-grade ML pipeline infrastructure: configures experiment tracking with MLflow or Weights & Biases, creates Kubeflow or Airflow DAGs for training…
pandas-pro
Performs pandas DataFrame operations for data analysis, manipulation, and transformation. Use when working with pandas DataFrames, data cleaning, aggregation, merging, or time…
kb-retriever
面向本地知识库目录的检索和问答助手。核心流程：(1)分层索引导航 (2)遇到PDF/Excel时必须先读取references学习处理方法 (3)处理文件后再检索。按文件类型组合使用 grep、Read、pdfplumber、pandas 进行渐进式检索，避免整文件加载。用户问题涉及"从知识库目录回答问题/检索信息/查资料"时使用。
code-exec-fallback
Fallback pattern for executing Python code when execute_code_sandbox fails
code-exec-fallback-266cba
Fallback workflow for reliable code execution when sandbox fails repeatedly
code-execution-fallback
Handle code execution failures with fallback strategies and anchored workspace paths
code-execution-fallback-e81068
Fallback workflow for executing Python code when execute_code_sandbox fails repeatedly
execute-code-fallback
Fallback from execute_code_sandbox to run_shell when e2b sandbox is unavailable
fallback-python-execution
Reliable Python execution workflow when execute_code_sandbox or shell_agent fail
fallback-python-shell
Use run_shell with Python heredoc when execute_code_sandbox or read_file fail
fallback-script-execution
Two-step script execution workflow for debugging when shell_agent and execute_code_sandbox consistently fail
prioritize-context-data
Ensures agents check and use provided context files for data before attempting external searches.
python-debug-execution-911f17
Debug Python script execution failures by capturing full tracebacks and verifying working directory
python-heredoc-fallback
Use shell Python heredoc as fallback when code sandbox fails
python-shell-workaround
Workaround for executing Python code with external packages when sandbox fails
python-spreadsheet-debug
Systematic Python debugging workflow for spreadsheet tasks to isolate environment issues from script logic
resilient-spreadsheet-workflow
Resilient multi-step workflow for spreadsheet processing when execute_code_sandbox fails, using shell_agent exploration, file-based scripts, and verification steps
sandbox-exec-fallback
Fallback pattern for executing Python code when execute_code_sandbox fails by writing to file and running via shell
sandbox-execution-fallback
Recover from execute_code_sandbox failures by writing Python scripts to files and executing via run_shell
sandbox-failure-recovery
Recover from execute_code_sandbox failures by writing code to file and executing via run_shell
sandbox-fallback-execution-048d5a
Fallback method to execute Python code when execute_code_sandbox fails with e2b errors
sandbox-fallback-python-e5d7ae
Fallback to run_shell with Python heredoc when execute_code_sandbox fails
shell-python-heredoc
Execute complex Python code via run_shell heredoc when execute_code_sandbox fails
web-search
This skill should be used when users need to search the web for information, find current content, look up news articles, search for images, or find videos. It uses DuckDuckGo's…
n8n-code-python
Write Python code in n8n Code nodes. Use when writing Python in n8n, using _input/_json/_node syntax, working with standard library, or need to understand Python limitations in…
large-file-parquet-analysis-and-highlight
当Excel文件总行数超过1万行时，通过转换为Parquet格式提升读取性能，提取目标指标并计算最大值，最后将结果输出为Excel并对特定行进行高亮标注。
category-filtering-and-difficulty-analysis
对Excel数据进行自定义分类统计、交叉分析与可视化，并基于多维度指标（如文本长度、术语密度、正则匹配等）进行综合评分与分级，适用于多类别数据分布统计及文本内容难度/质量评估场景。
category-statistics
提取指定类别列并统计各类别数量与占比，生成高分辨率的柱状图、饼图等组合可视化报告，适用于分类数据的分布情况分析。
categorical-comparison-analysis
对两类分类数据进行对比分析，统计数量差异与比例关系并生成可视化图表。
numeric-extraction-and-distribution-analysis
从带单位的字符串列中提取数值并清洗，生成包含直方图、饼图、条形图和累积分布图的多维度综合分布可视化图表，用于展示数据的集中趋势与分布特征。
excel-multi-sheet-threshold-analysis
统计多Sheet Excel总行数并根据规模选择处理策略，提取特定维度信息进行去重统计，并生成摘要与明细报表。
formatted-export-with-parquet
从多Sheet Excel文件中识别指定条件的记录，并将筛选结果以整行标红格式导出为Excel文件，适用于数据清洗、条件筛选与可视化标记场景。
grouped-statistics
对多 Sheet 的 Excel 文件进行行数统计、数据合并与前向填充。
statistical-distribution-and-outlier-analysis
执行数值型数据的分布分析与异常值检测，支持通过正则表达式从文本中提取误差项并生成高分辨率的箱线图与直方图报告。
invalid-data-cleaning
用于大规模Excel数据的预处理，通过统计总行数判断是否转换为Parquet格式以提升读写效率，并使用正则表达式清洗指定文本列（如仅保留中文字符），最后导出清洗后的文件并提供下载链接。
large-excel-analysis-and-formatting
用于处理多Sheet大型Excel文件，支持大文件Parquet格式转换提速，并使用openpyxl生成带条件高亮和自定义样式的格式化Excel报告及下载链接。
line-chart-visualization
提取结构化数据并进行特征清洗与聚类分析，生成包含趋势对比、分布特征与参数敏感性的多维度综合可视化图表，适用于各类趋势预测与多维对比场景。
multi-file-excel-parquet-analysis
读取多 Sheet Excel 文件并统计规模，支持大文件向 Parquet 格式转换、分类数据统计及可视化报告生成。
multi-sheet-reading-and-analysis
用于读取多工作表Excel文件，动态评估数据量以启用Parquet大文件优化，并执行正则清洗、分类汇总、线性拟合及生成带格式的图表与结果文件。
excel-outlier-detection-and-highlighting
识别 Excel 中的超限数值与错误单元格并进行高亮标注。
outlier-detection-and-quality-assessment
执行全面的异常值检测与数据质量评估，利用 IQR 方法识别异常值并结合偏度、峰度分析数据分布特征，适用于非正态分布数据的预处理阶段。
pdf-analysis
PDF 文档解析。自动区分文字型 PDF 与扫描型 PDF，覆盖：文本/表格提取、多页全量扫描、嵌入图表 caption、单位感知数值计算。
pie-chart-data-analysis
对多Sheet Excel或CSV数据进行分类汇总统计，自动识别关键字段并生成包含占比、数值及美化饼图的可下载分析报告。
pivot-table-cross-analysis
利用交叉表与热力图对分类数据进行多维度占比分析，适用于奖项分布、绩效评估或市场占有率等结构化数据的清洗与可视化。
ppt-analysis
PPT (.pptx/.ppt) 全量解析。覆盖：所有 slide 文本/表格/图表提取、嵌入图片 caption、纯图片 slide 渲染识别、数据标签提取。
excel-conditional-filtering-optimization
根据多维数值条件筛选 Excel 数据并导出结果，支持大规模数据的自动性能优化处理。
single-sheet-reading-and-analysis
读取并解析单个Excel工作表数据，支持合并单元格处理、数据清洗、交叉分析及多维度可视化，适用于需要从单表中提取关键指标并进行趋势模拟与图表生成的场景。
sn-da-excel-workflow
Excel 数据分析多步编排器。覆盖：(1) 读取多 Sheet Excel 文件并统计行数，(2) 大文件检测（≥10k 行自动 Parquet 优化），(3) 数据清洗（缺失值、文本标准化、无效字符），(4) 条件筛选与分类提取，(5) 跨 Sheet 统计聚合，(6) 导出 Excel/CSV…
sn-da-large-file-analysis
万行以上 Excel 数据集的高性能分析引擎。提供 openpyxl read_only 流式读取（iter_rows 支持 10 万行以上）、Parquet 转换加速、内存优化、分块处理和大文件写入模式。**遇到以下任一情况就主动使用本 skill**：①数据行数 ≥ 10k（由 sn-da-excel-workflow…
sn-search-code
用于查找代码示例、开源项目、GitHub Issue、技术问答、开发者讨论、HuggingFace 模型/数据集/Space。
sn-search-social-en
用于搜索英文社交平台，包括 Reddit 帖子、Twitter/X 推文和 YouTube 视频。
excel-multi-sheet-dynamic-analysis
用于分析包含多个Sheet的Excel文件，动态判断数据量级以决定是否转换为Parquet进行大文件处理，并支持跨Sheet的特定字段统计、数据清洗、交叉分析与可视化，最终生成带下载链接的汇总报告。
stacked-chart-visualization
处理包含百分比字符串的分类占比数据，通过补全缺失维度并生成堆叠柱状图，直观展示多维度构成随时间或分类的变化趋势。
large-file-conditional-formatting
根据Excel总行数自动切换Parquet加速读取，计算特定维度的时间序列平均值，并使用openpyxl输出带有条件格式（如低于均值标绿）和自定义样式的分析报告。
excel-threshold-analysis-and-styling
根据 Excel 数据量级自动判断处理策略，执行数值列清洗、条件过滤，并使用 openpyxl 对符合条件的单元格进行样式标记与导出。
time-series-and-categorical-analysis
对时间序列或分类数据进行多维度趋势分析、百分比清洗、绩效分级建模与预测，并生成高分辨率的可视化综合报告，适用于业务指标监控与预测场景。
trend-analysis
基于多维度数据进行分级评估与趋势预测，通过设定差异化增长率计算预测值，并生成对比可视化图表，适用于绩效评估、目标设定等场景。
word-analysis
Word (.docx/.doc) 文档全量解析。覆盖：正文/段落文本提取、表格数据提取、高亮/颜色格式读取、多文件汇总对比、嵌入图片转 caption。
technology-selection
Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI (MEAI), Microsoft Agent Framework (MAF), GitHub…
chart-rendering
Visualise the result of an analysis as a chart (line, bar, area, scatter, etc.). Use when the user asks to "plot...", "chart...", "show me the trend of...", "visualise...", or…
python-repl
Interactive Python REPL automation with common helpers and best practices
stock-analysis
股票个股分析，实时获取价格涨跌幅，计算技术指标和支撑位，识别缺口并判断支撑压力，智能预测未来3天走势并给出操作建议
generate-rag-dataset
Generate a synthetic evaluation dataset from your RAG knowledge base. Creates diverse Q&A pairs with expected answers and relevant context, ready for LangWatch experiments and…
data-analytics
Create data pipeline and analytics architecture diagrams using PlantUML syntax with database/analytics stencil icons. Best for ETL pipelines, data lakes, real-time streaming…
uv-package-manager
Master the uv package manager for fast Python dependency management, virtual environments, and modern Python project workflows. Use when setting up Python projects, managing…
literature-review
帮助用户撰写高质量的文献综述类论文。提供从选题、文献检索、评估筛选、结构规划到最终写作的全流程指导。适用于需要撰写独立文献综述论文或学术论文中文献综述部分的用户。
StatsPAI_skill
Use when the user asks to run a full empirical / causal analysis in Python — by default in the style of an applied economics paper (AER / QJE / JPE / ReStud / AEJ) with DID / RD…
python-econ-computing
Use when writing Python code for DSGE models, HANK models, numerical economic computation, causal inference, or quantitative economic data analysis
ai-ml-skills
27 ai & machine learning skills. Trigger: ML experiments, model training, deep learning, NLP, computer vision. Design: covers frameworks, benchmarks, paper reproduction, and AI…
ai-model-benchmarking
Benchmark AI models across 60+ academic evaluation suites and metrics
ai-scientist-v2-guide
Automated scientific discovery via agentic tree search by Sakana AI
anomaly-detection-papers-guide
Industrial anomaly detection methods and benchmark papers
anystyle-api
Citation reference parser using machine learning
architecture-design
Use only when creating new registrable ML components that require Factory or Registry patterns.
auto-review-loop-minimax
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with \"auto review loop…
bibliography-management-guide
Manage references with BibLaTeX, natbib, and LaTeX bibliography styles
bibtex-management-guide
Clean, format, deduplicate, and manage BibTeX bibliography files for LaTeX
bokeh-visualization-guide
Guide to Bokeh for interactive browser-based research visualizations
causal-inference-guide
Causal inference methods including DiD, IV, RDD, and synthetic control
causal-ml
Reference for semiparametric ML estimators: DML with cross-fitting, generalized random forests, debiased regularization, and nuisance function approximation. Covers…
check-env
Verifies required tools (Quarto, uv, Python, R, Stata, TeX) and Jupyter kernels are installed. Use when setting up or troubleshooting.
citation-network-builder
Build and analyze citation networks from academic reference data
codebook
Auto-generates a Markdown codebook from a dataset (CSV, DTA, Excel, Parquet) with types and summary statistics. Use when documenting variables.
codebook-pass
调查数据清洗Skill。处理调查数据（CGSS/CHIP/CSS等）时的标准化清洗流程，包括缺失值处理、变量编码统一、数据异常值检测。触发词：数据清洗/调查数据/codebook/数据清洗流程/问卷数据处理
computational-chemistry-guide
DFT, molecular simulation, and reaction prediction tools for chemists
conciseness-editing-guide
Eliminate wordiness and redundancy in academic prose for clarity
cross-disciplinary-ideation
Field connection mapping and systematic ideation for method transfer
csv-data-analyzer
Load, explore, clean, and analyze CSV data with statistical summaries
data-anomaly-detection
Detect anomalies and outliers in research data using statistical methods
data-cleaning-pipeline
Systematic data cleaning workflows for research datasets
data-cog-guide
Upload messy CSVs with minimal prompting for deep automated analysis
data-scientist
Rigorous data science methodology and mindset for Python research. Covers EDA, data validation, transformation verification, documentation standards, visualization design…
dataset-finder-guide
Search and download research datasets from Kaggle, HuggingFace, and repos
dataviz-skills
14 data visualization skills. Trigger: charts, plots, figures, publication-quality graphics. Design: one skill per tool with code templates and academic formatting conventions.
document-skills
10 document processing skills. Trigger: extracting text from PDFs, parsing references, document Q&A. Design: parsing pipelines (GROBID, marker) and structured extraction tools.
env-snapshot
Captures tool versions, packages, and kernel info as a reproducibility record in notes/. Use when documenting the environment.
experimental-design-guide
Design rigorous experiments using DOE, factorial designs, and response surfaces
geopandas
geopandas spatial data library for Python: manipulation, analysis, and visualization of geographic data. Covers GeoDataFrames, spatial joins, CRS/projections, vector operations…
geospatial-viz-guide
Create maps, choropleths, and spatial data visualizations for research
google-colab-guide
Run and manage Google Colab notebooks for Python and ML research
grad-school-guide
Practical advice for thriving in PhD programs and academic research
grobid-pdf-parsing
Extract structured text, metadata, and references from academic PDFs
huggingface-inference-guide
Run NLP and CV model inference via Hugging Face free-tier API
innovation-management-guide
Innovation metrics, R&D management research, and technology forecasting
interactive-viz-guide
Interactive data visualization with Plotly, ECharts, and D3
iv-regression-guide
Apply instrumental variables, 2SLS, and address endogeneity issues
json-data-visualizer
Guide to JSON Crack for visualizing complex JSON data structures
jupyter-notebook-guide
Best practices for computational research notebooks with reproducible workflows
kaggle-learner
This skill should be used when the user asks to "learn from Kaggle", "study Kaggle solutions", "analyze Kaggle competitions", or mentions Kaggle competition URLs. Provides access…
kedro-pipeline-guide
Build reproducible data science pipelines with Kedro for research projects
lens-scholarly-api
Search 300M+ scholarly and patent records via the Lens.org API
llm-from-scratch-guide
Build a ChatGPT-like LLM from scratch using PyTorch step by step
metabase-analytics-guide
Guide to Metabase for open-source research data analytics and dashboards
methods-section-guide
Guide to writing clear and reproducible methodology sections
missing-data-handling
Diagnose missing data patterns and apply appropriate imputation strategies
ml-causal
This skill covers modern ML-based causal inference methods: Causal Forests (GRF) for heterogeneous treatment effects, Double/Debiased Machine Learning (DML) for partially linear…
ml-experiment-tracker
Plan reproducible ML experiment runs with parameters and metrics tracking
ml-pipeline-guide
Build and deploy reproducible production ML pipelines for research
open-semantic-search-guide
Self-hosted semantic search and text mining platform
pandas-data-wrangling
Data cleaning, transformation, and exploratory analysis with pandas
papers-we-love-guide
Community-curated directory of influential CS research papers
patent-analysis-guide
Patent search, classification, landscape analysis, and prior art mining
Full-empirical-analysis-skill
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest + rdrobust + econml…
plotly-interactive-guide
Guide to Plotly.py for interactive scientific visualizations in Python
polars
Polars DataFrame library for high-performance data manipulation in Python. Covers lazy/eager execution, expressions, I/O (CSV, Parquet, JSON, database), aggregations, joins…
prompt-engineering-research
Systematic prompt engineering methods for AI-assisted academic research workf...
python-causality-guide
Learn causal inference with Python using the Brave and True handbook
python-reproducibility-guide
Reproducible Python environments, notebooks, and literate programming
reinforcement-learning-guide
Reinforcement learning fundamentals, algorithms, and research
running-causalpy-experiments
Fit, summarize, plot, and interpret a chosen CausalPy experiment. Use after the causal method has been selected, including when configuring PyMC/sklearn models and scale-aware…
science-communication
Translating technical data science findings for non-technical audiences. Covers audience analysis, narrative frameworks (Pyramid Principle, SCQA, AIDA), plain-language…
scikit-learn
General-purpose machine learning with scikit-learn. Covers unsupervised methods (clustering, GMM, PCA, t-SNE, UMAP, manifold learning, evaluation metrics), supervised methods…
species-distribution-guide
Species distribution modeling with MaxEnt, SDM methods, and GBIF data
stat-writing
stat-writing
statistical-modeling
Use when estimating a statistical or econometric model, running a regression, specifying an identification strategy, testing a hypothesis, or fitting any model to empirical data.…
streamline-analyst-guide
End-to-end data analysis AI agent with Streamlit UI
survey-data-processing
Clean, recode, and prepare survey response data for analysis
svy
svy: design-based analysis of complex survey data in Python. Covers survey design specification (strata, PSU, weights, FPC), variance estimation (Taylor linearization, BRR…
tensorflow-guide
TensorFlow best practices for tf.function, GPU memory, and deployment
topology-data-analysis
Topological data analysis: persistent homology, Mapper, and TDA tools
wrangling-skills
10 data wrangling skills. Trigger: messy data, format conversion, missing values, data reshaping. Design: pipeline-oriented recipes for common data cleaning and transformation…
zotero-actions-tags-guide
Zotero workflow automation with custom actions and tags
zotero-mcp-guide
Guide to Zotero MCP for connecting Zotero library with AI assistants
pyzotero
Interact with Zotero reference management libraries using the pyzotero Python client. Retrieve, create, update, and delete items, collections, tags, and attachments via the…
polars
Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow…
scikit-learn
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality…
aeon
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity…
anndata
This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata…
arboreto
Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell…
bio-admet-prediction
Predicts ADMET properties using ADMETlab 3.0 API or DeepChem models. Estimates bioavailability, CYP inhibition, hERG liability, and 119 toxicity endpoints with uncertainty…
bio-atac-seq-atac-qc
Quality control metrics for ATAC-seq data including fragment size distribution, TSS enrichment, FRiP, and library complexity. Use when assessing ATAC-seq library quality before…
bio-atac-seq-differential-accessibility
Find differentially accessible chromatin regions between conditions using DiffBind or DESeq2. Use when comparing chromatin accessibility between treatment groups, cell types, or…
bio-atac-seq-footprinting
Detect transcription factor binding sites through footprinting analysis in ATAC-seq data using TOBIAS. Use when identifying TF occupancy patterns within accessible regions, as TF…
bio-chipseq-motif-analysis
De novo motif discovery and known motif enrichment analysis using HOMER and MEME-ChIP. Identify transcription factor binding motifs in ChIP-seq, ATAC-seq, or other genomic peak…
bio-copy-number-cnv-visualization
Visualize copy number profiles, segments, and compare across samples. Create publication-quality plots of CNV data from CNVkit, GATK, or other callers. Use when creating…
bio-crispr-screens-base-editing-analysis
Analyzes base editing and prime editing outcomes including editing efficiency, bystander edits, and indel frequencies. Use when quantifying CRISPR base editor results, comparing…
bio-crispr-screens-batch-correction
Batch effect correction for CRISPR screens. Covers normalization across batches, technical replicate handling, and batch-aware analysis. Use when combining screens from multiple…
bio-crispr-screens-crispresso-editing
CRISPResso2 for analyzing CRISPR gene editing outcomes. Quantifies indels, HDR efficiency, and generates comprehensive editing reports. Use when analyzing amplicon sequencing…
bio-crispr-screens-hit-calling
Statistical methods for calling hits in CRISPR screens. Covers MAGeCK, BAGEL2, drugZ, and custom approaches for identifying essential and resistance genes. Use when identifying…
bio-crispr-screens-library-design
CRISPR library design for genetic screens. Covers sgRNA selection, library composition, control design, and oligo ordering. Use when designing custom sgRNA libraries for…
bio-crispr-screens-mageck-analysis
MAGeCK (Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout) for pooled CRISPR screen analysis. Covers count normalization, gene ranking, and pathway analysis. Use when…
bio-crispr-screens-screen-qc
Quality control for pooled CRISPR screens. Covers library representation, read distribution, replicate correlation, and essential gene recovery. Use when assessing screen quality…
bio-ctdna-mutation-detection
Detects somatic mutations in circulating tumor DNA using variant callers optimized for low allele fractions with UMI-based error suppression. Reliably detects mutations at VAF…
bio-differential-splicing
Detects differential alternative splicing between conditions using rMATS-turbo (BAM-based) or SUPPA2 diffSplice (TPM-based). Reports events with FDR-corrected significance and…
bio-epidemiological-genomics-amr-surveillance
Detect and track antimicrobial resistance genes using AMRFinderPlus and ResFinder with epidemiological context. Monitor resistance trends and identify emerging resistance…
bio-epidemiological-genomics-pathogen-typing
Perform multi-locus sequence typing (MLST), core genome MLST, and SNP-based strain typing for bacterial isolate characterization using mlst and chewBBACA. Use when identifying…
bio-epidemiological-genomics-transmission-inference
Infer pathogen transmission networks and identify likely transmission pairs using TransPhylo and outbreak reconstruction algorithms. Estimate who-infected-whom from genomic and…
bio-epidemiological-genomics-variant-surveillance
Assign pathogen lineages and track variants using Nextclade and pangolin for viral surveillance. Monitor variant prevalence and identify emerging variants of concern. Use when…
bio-fragment-analysis
Analyzes cfDNA fragment size distributions and fragmentomics features using FinaleToolkit or Griffin. Extracts nucleosome positioning patterns, fragment ratios, and DELFI-style…
bio-genome-engineering-off-target-prediction
Predict CRISPR off-target sites using Cas-OFFinder and CFD scoring algorithms. Identify potential unintended cleavage sites genome-wide and assess guide specificity. Use when…
bio-hi-c-analysis-compartment-analysis
Detect A/B compartments from Hi-C data using cooltools and eigenvector decomposition. Identify active (A) and inactive (B) chromatin compartments from contact matrices. Use when…
bio-hi-c-analysis-contact-pairs
Process Hi-C read pairs using pairtools. Parse alignments, filter duplicates, classify pairs, and generate contact statistics from Hi-C sequencing data. Use when processing raw…
bio-hi-c-analysis-hic-data-io
Load, convert, and manipulate Hi-C contact matrices using cooler format. Read .cool/.mcool files, convert from .hic format, access matrix data, and export to different formats.…
bio-hi-c-analysis-hic-differential
Compare Hi-C contact matrices between conditions to identify differential chromatin interactions. Compute log2 fold changes, statistical significance, and visualize differential…
bio-hi-c-analysis-hic-visualization
Visualize Hi-C contact matrices, TADs, loops, and genomic features using matplotlib, cooltools, and HiCExplorer. Create triangle plots, virtual 4C, and multi-track figures. Use…
bio-hi-c-analysis-loop-calling
Detect chromatin loops and point interactions from Hi-C data using cooltools, chromosight, and HiCCUPS-like methods. Identify CTCF-mediated loops and enhancer-promoter contacts.…
bio-hi-c-analysis-matrix-operations
Balance, normalize, and transform Hi-C contact matrices using cooler and cooltools. Apply iterative correction (ICE), compute expected values, and generate observed/expected…
bio-hi-c-analysis-tad-detection
Call topologically associating domains (TADs) from Hi-C data using insulation score, HiCExplorer, and other methods. Identify domain boundaries and hierarchical domain structure.…
bio-imaging-mass-cytometry-cell-segmentation
Cell segmentation from multiplexed tissue images. Covers deep learning (Cellpose, Mesmer) and classical approaches for nuclear and whole-cell segmentation. Use when extracting…
bio-imaging-mass-cytometry-data-preprocessing
Load and preprocess imaging mass cytometry (IMC) and MIBI data. Covers MCD/TIFF handling, hot pixel removal, and image normalization. Use when starting IMC analysis from raw MCD…
bio-imaging-mass-cytometry-interactive-annotation
Interactive cell type annotation for IMC data. Covers napari-based annotation, marker-guided labeling, training data generation, and annotation validation. Use when manually…
bio-imaging-mass-cytometry-phenotyping
Cell type assignment from marker expression in IMC data. Covers manual gating, clustering, and automated classification approaches. Use when assigning cell types to segmented IMC…
bio-imaging-mass-cytometry-quality-metrics
Quality metrics for IMC data including signal-to-noise, channel correlation, tissue integrity, and acquisition QC. Use when assessing data quality before analysis or…
bio-imaging-mass-cytometry-spatial-analysis
Spatial analysis of cell neighborhoods and interactions in IMC data. Covers neighbor graphs, spatial statistics, and interaction testing. Use when analyzing spatial relationships…
bio-immunoinformatics-epitope-prediction
Predict B-cell and T-cell epitopes using BepiPred, IEDB tools, and structure-based methods for vaccine and antibody design. Identify immunogenic regions in antigens. Use when…
bio-immunoinformatics-immunogenicity-scoring
Score and prioritize neoantigens and epitopes for immunogenicity using multi-factor models combining MHC binding, processing, expression, and sequence features. Rank candidates…
bio-immunoinformatics-mhc-binding-prediction
Predict peptide-MHC class I and II binding affinity using MHCflurry and NetMHCpan neural network models. Identify potential T-cell epitopes from protein sequences. Use when…
bio-immunoinformatics-neoantigen-prediction
Identify tumor neoantigens from somatic mutations using pVACtools for personalized cancer immunotherapy. Predict mutant peptides that bind patient HLA and may elicit T-cell…
bio-immunoinformatics-tcr-epitope-binding
Predict TCR-epitope specificity using ERGO-II and deep learning models for T-cell receptor antigen recognition. Match TCRs to their cognate epitopes or predict TCR targets. Use…
bio-long-read-sequencing-isoseq-analysis
Analyze PacBio Iso-Seq data for full-length isoform discovery and quantification. Use when characterizing transcript diversity or identifying novel splice variants.
bio-metabolomics-lipidomics
Specialized lipidomics analysis for lipid identification, quantification, and pathway interpretation. Covers LC-MS lipidomics with LipidSearch, MS-DIAL, and LipidMaps annotation.…
bio-metabolomics-metabolite-annotation
Metabolite identification from m/z and retention time. Covers database matching, MS/MS spectral matching, and confidence level assignment. Use when assigning compound identities…
bio-metabolomics-msdial-preprocessing
MS-DIAL-based metabolomics preprocessing as alternative to XCMS. Covers peak detection, alignment, annotation, and export for downstream analysis. Use when processing MS-DIAL…
bio-metabolomics-targeted-analysis
Targeted metabolomics analysis using MRM/SRM with standard curves. Covers absolute quantification, method validation, and quality assessment. Use when quantifying specific…
bio-metagenomics-abundance
Species abundance estimation using Bracken with Kraken2 output. Redistributes reads from higher taxonomic levels to species for more accurate estimates. Use when accurate…
bio-metagenomics-functional-profiling
Profile functional potential of metagenomes using HUMAnN3 and similar tools. Use when obtaining pathway abundances, gene family counts, or functional annotations from metagenomic…
bio-metagenomics-kraken
Taxonomic classification of metagenomic reads using Kraken2. Fast k-mer based classification against RefSeq database. Use when performing initial taxonomic classification of…
bio-metagenomics-metaphlan
Marker gene-based taxonomic profiling using MetaPhlAn 4. Provides accurate species-level relative abundances using clade-specific markers. Use when accurate taxonomic profiling…
bio-metagenomics-strain-tracking
Track bacterial strains using MASH, sourmash, fastANI, and inStrain. Compare genomes, detect contamination, and monitor strain-level variation. Use when needing sub-species…
bio-metagenomics-visualization
Visualize metagenomic profiles using R (phyloseq, microbiome) and Python (matplotlib, seaborn). Create stacked bar plots, heatmaps, PCA plots, and diversity analyses. Use when…
bio-methylation-based-detection
Analyzes cfDNA methylation patterns for cancer detection using cfMeDIP-seq or bisulfite sequencing with MethylDackel. Identifies cancer-specific methylation signatures and…
bio-methylation-calling
Extract methylation calls from Bismark BAM files using bismark_methylation_extractor. Generates per-cytosine reports for CpG, CHG, and CHH contexts. Use when extracting…
bio-microbiome-functional-prediction
Predict metagenome functional content from 16S rRNA marker gene data using PICRUSt2. Infer KEGG, MetaCyc, and EC abundances from ASV tables. Use when functional profiling is…
bio-molecular-descriptors
Calculates molecular descriptors and fingerprints using RDKit. Computes Morgan fingerprints (ECFP), MACCS keys, Lipinski properties, QED drug-likeness, TPSA, and 3D conformer…
bio-orchestrator
Meta-agent that routes bioinformatics requests to specialised sub-skills. Handles file type detection, analysis planning, report generation, and reproducibility export.
bio-proteomics-data-import
Load and parse mass spectrometry data formats including mzML, mzXML, and quantification tool outputs like MaxQuant proteinGroups.txt. Use when starting a proteomics analysis with…
bio-proteomics-dia-analysis
Data-independent acquisition (DIA) proteomics analysis with DIA-NN and other tools. Use when analyzing DIA mass spectrometry data with library-free or library-based workflows for…
bio-proteomics-differential-abundance
Statistical testing for differentially abundant proteins between conditions. Covers limma and MSstats workflows with multiple testing correction. Use when identifying proteins…