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O SkillsMP coletou 26 skills de CRAG666/dotfiles. Abra uma skill para revisar a origem e os detalhes.
Mostrando 26 de 26 skills coletadas.
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…
Idioma do texto original: inglês
Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation…
Idioma do texto original: inglês
Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or…
Idioma do texto original: inglês
Convert heterogeneous documents and selected URIs to Markdown with Microsoft MarkItDown for text analysis, search, and LLM/RAG ingestion. Covers safe local conversion, streams, Office/PDF/data formats, batch workflows, plugins, vision OCR, Azure extraction,…
Idioma do texto original: inglês
Low-level plotting library for full customization. Use when you need fine-grained control over every plot element, creating novel plot types, or integrating with specific scientific workflows. Export to PNG/PDF/SVG for publication. For quick statistical plots…
Idioma do texto original: inglês
Create, analyze, and visualize 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…
Idioma do texto original: inglês
Use NeuroKit2 to build or audit reproducible research workflows for physiological time-series preprocessing, event/interval analysis, multimodal alignment, variability, and complexity. Trigger when code imports neurokit2 or needs its current APIs, schemas,…
Idioma do texto original: inglês
GPU-accelerates scientific Python on NVIDIA hardware and verifies that the result is correct and faster. Use for CUDA/GPU optimization; CPU-bound NumPy, SciPy, pandas, scikit-learn, NetworkX, scikit-image, vector-search, image-processing, graph, simulation,…
Idioma do texto original: inglês
Search 11 academic literature APIs for papers, preprints, citations, and open-access full text, and return results with reproducible provenance. Covers PubMed, PMC (full text), Europe PMC (full-text and preprint search), bioRxiv, medRxiv, arXiv, OpenAlex,…
Idioma do texto original: inglês
Prior art patent search via Google Patents' JSON endpoint and Lens.org, with PDF download. Use when the user asks to search patents, prior art, "anterioridad", "patentes ancla", freedom-to-operate, novelty context, or patent landscaping. Covers query syntax,…
Idioma do texto original: inglês
High-performance genomic interval operations and bioinformatics file I/O on Polars DataFrames. Overlap, nearest, merge, coverage, complement, subtract for BED/VCF/BAM/GFF intervals. Streaming, cloud-native, faster bioframe alternative.
Idioma do texto original: inglês
High-performance DataFrame library for Python ETL, analytics, and pandas migration. Use for expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU…
Idioma do texto original: inglês
STRICT: stdlib idioms are mandatory — reinventing a stdlib feature is a defect, not a style choice. Apply whenever the user writes, refactors, optimizes, or reviews Python, including one-liners and code-review feedback. Verify non-trivial stdlib APIs against…
Idioma do texto original: inglês
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,…
Idioma do texto original: inglês
Create and audit truthful, accessible, publication-ready scientific figures with Matplotlib, Seaborn, or Plotly. Use for figure design, multi-panel layouts, uncertainty and missing-data displays, color/contrast review, image metadata validation, and journal…
Idioma do texto original: inglês
Use whenever the user writes, drafts, revises, edits, polishes, or translates scientific or academic prose in ENGLISH - Q1 research articles, theses, dissertations, abstracts, introductions, methods, results, discussions, conclusions, acknowledgments,…
Idioma do texto original: inglês
Biological data toolkit. Sequence analysis, alignments, phylogenetic trees, diversity metrics (alpha/beta, UniFrac), ordination (PCoA), PERMANOVA, FASTA/Newick I/O, for microbiome analysis.
Idioma do texto original: inglês
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML…
Idioma do texto original: inglês
Build, evaluate, and audit right-censored or competing-risk survival workflows with scikit-survival, including leakage-safe preprocessing, model selection, probability prediction, and censoring-aware metrics.
Idioma do texto original: inglês
Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive…
Idioma do texto original: inglês
Explain and audit machine-learning predictions with SHAP. Use for selecting SHAP explainers and maskers, computing and validating feature attributions, handling multi-output explanations, and producing local or global SHAP visualizations.
Idioma do texto original: inglês
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…
Idioma do texto original: inglês
Personal default directives for any generated or edited code: check for an existing library before writing anything, then emit the smallest correct code with no AI filler. Apply whenever writing, editing, refactoring, or emitting code in any language — new…
Idioma do texto original: inglês
STRICT structure-and-complexity layer for non-trivial code work: designing systems, writing new modules, refactoring, implementing algorithms, or making structural decisions. Complements code-style-defaults (form of the output) and python-native (Python…
Idioma do texto original: inglês
Enforces rigorous scientific methodology for machine learning experiments intended to support publication-grade claims (Q1 journals, conference papers, regulated decisions). Use this skill when designing an ML pipeline, splitting datasets, evaluating…
Idioma do texto original: inglês
Usar siempre que el usuario escriba, redacte, revise o traduzca texto científico/académico en ESPAÑOL: artículos, papers, tesis, abstracts, introducciones, metodologías, resultados, discusión, conclusiones, agradecimientos, revisiones de literatura, defensas,…
Idioma do texto original: espanhol