Lzy599775/agent-auto-sci-skills
Skill Codex
A research workflow for building and checking machine-learning and artificial-intelligence models, including models that work with maps, time-based data, text, or images.
Lzy599775/agent-auto-sci-skills
Skill Codex
A research workflow for building and checking machine-learning and artificial-intelligence models, including models that work with maps, time-based data, text, or images.
Lzy599775/agent-auto-sci-skills
Skill Codex
A guide for turning research projects into lasting local workflows with source tracking, structured notes, experiments, paper planning, reviews, and checkpoints. It also describes a shared memory system for research materials.
Lzy599775/agent-auto-sci-skills
Skill Codex
A workflow for exploring data, choosing statistical tests, and creating clear charts, tables, maps, and dashboards for research.
Lzy599775/agent-auto-sci-skills
Skill Codex
A guide for working with geographic and satellite data, including maps, location-based measurements, and spatial analysis. It covers common tools such as GeoPandas, which handles geographic data in Python.
Lzy599775/agent-auto-sci-skills
Skill Codex
A research-planning and critical-thinking workflow for turning broad ideas into testable questions and defensible studies.
Lzy599775/agent-auto-sci-skills
Skill Codex
A skill for planning and writing scientific papers, reviews, posters, presentations, cover letters, and replies to peer reviewers.
Lzy599775/agent-auto-sci-skills
Skill Codex
A coordinating skill for managing a complete research workflow, from choosing a topic and finding literature to analysis, figures, manuscript writing, review, submission, and later revisions.
Lzy599775/agent-auto-sci-skills
Skill Codex
A writing guide for English papers in geography, remote sensing, urban exposure, spatial fairness, and related fields. Remote sensing uses measurements from satellites or other sensors to study places and environmental conditions.
Lzy599775/agent-auto-sci-skills
Skill Codex
A selected toolkit for exploring data, running statistical analysis, and creating scientific charts. It covers tools such as Matplotlib, Seaborn, NetworkX, Polars, and Dask, with guidance for publication-ready figures.
Lzy599775/agent-auto-sci-skills
Skill Claude Code
Scales pandas, NumPy, and custom Python research workflows beyond memory or across clusters with Dask. Covers DataFrames, Arrays, Bags, Futures, chunking, schedulers, and distributed diagnostics. Use for partitioned file processing, scientific array computation, or parallel tasks whose memory and dependency structure…
Lzy599775/agent-auto-sci-skills
Skill Claude Code
Performs bounded, local exploratory analysis of explicitly supported scientific files. Supports redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…
Lzy599775/agent-auto-sci-skills
Skill Claude Code
Creates and customizes scientific plots with Matplotlib. Used for fine-grained control over plot elements, novel plot types, and scientific workflows. Export to PNG/PDF/SVG for publication. For quick statistical plots use seaborn; for interactive plots use plotly; for publication-ready multi-panel figures with journal…
Lzy599775/agent-auto-sci-skills
Skill Claude CodeCodex
Creates, analyzes, and visualizes complex networks and graphs in Python with NetworkX. Use when working with network/graph data structures, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks (random, scale-free, small-world), reading/writing graph…
Lzy599775/agent-auto-sci-skills
Skill Claude Code
High-performance DataFrame library for Python ETL, analytics, and pandas migration. It supports expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.
Lzy599775/agent-auto-sci-skills
Skill Claude Code
Creates and audits truthful, accessible, publication-ready scientific figures with Matplotlib, Seaborn, or Plotly. Use it for figure design, multi-panel layouts, uncertainty and missing-data displays, color/contrast review, image metadata validation, and journal export planning.
Lzy599775/agent-auto-sci-skills
Skill Claude Code
Creates Seaborn statistical visualizations with pandas integration for distributions, relationships, categorical comparisons, regression displays, pair plots, and heatmaps. Supports function and objects interfaces with explicit aggregation, uncertainty, and missing-data handling. Best suited to static exploratory…
Lzy599775/agent-auto-sci-skills
Skill Claude CodeCodex
Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze experimental or survey data, check statistical assumptions, compute required…
Lzy599775/agent-auto-sci-skills
Skill Codex
A toolkit for geospatial science and remote sensing, the analysis of information collected about Earth from satellites or other sensors. It covers geographic data, maps, spatial analysis, and related research workflows.
Lzy599775/agent-auto-sci-skills
Skill Claude CodeCodex
Supports geospatial research workflows for remote sensing, vector and raster GIS, spatial statistics, terrain and network analysis, and machine learning for Earth observation. Use when processing satellite imagery, aligning coordinate systems and raster grids, accessing STAC catalogs, analyzing geospatial time series…
Lzy599775/agent-auto-sci-skills
Skill Claude Code
Guidance and local audit tools for Python workflows that directly use GeoPandas GeoSeries, GeoDataFrame, spatial operations, or vector-data I/O.
Lzy599775/agent-auto-sci-skills
Skill Codex
A selected toolkit of machine-learning and artificial-intelligence guidance for libraries and methods such as scikit-learn, PyTorch Lightning, Transformers, SHAP, time-series forecasting, graph learning, and UMAP.
Lzy599775/agent-auto-sci-skills
Skill Claude Code
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard…
Lzy599775/agent-auto-sci-skills
Skill Claude Code
Deep learning framework (PyTorch Lightning / lightning package). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard, MLflow), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.
Lzy599775/agent-auto-sci-skills
Skill Claude Code
Supports machine learning in Python with scikit-learn. Applies when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference…
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