Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.
Complete mass spectrometry analysis platform. Use for proteomics workflows feature detection, peptide identification, protein quantification, and complex LC-MS/MS pipelin — from…
Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological — from…
Write research/technical reports with strong structure + figure standards. Supports Markdown/HTML/PDF outputs (Quarto optional), executive summary, methods, results, discussion,…
Use for scientific or scholarly research with source traceability, literature reviews, paper discovery, arXiv/OpenAlex/Crossref/Europe PMC/Semantic Scholar/PubMed queries, corpus…
科研助手基于134个科学技能库,提供从文献检索到论文发表的全流程科研支持,核心功能包括文献检索与综述(PubMed/Google…
Comprehensive scientific document review and analysis. Use when Claude needs to review scientific papers, reports, preprints, or other research documents for: (1) Identifying and…
Analyze Kuhn's paradigm shifts as historical narrative: the Copernican revolution, Newton, Darwin, Einstein, quantum mechanics, plate tectonics, and the genomic revolution.
Create publication-quality scientific diagrams using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.1 Pro Preview for quality review.
Create publication-quality scientific diagrams using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review.
Build slide decks and presentations for research talks. Use this for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis def — from…
Biological data toolkit. Sequence analysis, alignments, phylogenetic trees, diversity metrics (alpha/beta, UniFrac), ordination (PCoA), PERMANOVA, FASTA/Newick I/O, for m — from…
Biological data toolkit. Sequence analysis, alignments, phylogenetic trees, diversity metrics (alpha/beta, UniFrac), ordination (PCoA), PERMANOVA, FASTA/Newick I/O, for m — from…
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality re — from…
Deep generative models for single-cell omics. Use when you need probabilistic batch correction (scVI), transfer learning, differential expression with uncertainty, or mul — from…
Comprehensive scientific research toolkit with 139 specialized skills for biology, chemistry, medicine, data science, and computational research.
Build slide decks and presentations for research talks. Use this for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis def — from…
Build slide decks and presentations for research talks. Use this for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis def — from…
Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API.
Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference.
Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference.
Query STRING API for protein-protein interactions (59M proteins, 20B interactions). Network analysis, GO/KEGG enrichment, interaction discovery, 5000+ species, for system — from…
Create or substantially refine publication-grade scientific and technical SVG figures for reports, slides, README/docs, and DOCX/PDF workflows.
Use when you are starting a new mass spectrometry analysis task or feature request where the problem scope is unclear, the tool chain (e.g., OpenMS + Python + KNIME integration)…
Bilimsel metod, hipotez, kanıt değerlendirme, bias analizi. ⚠️ Araştırma/analiz için kullan. Mimari karar için → ultrathink-core.
Analyze datasets to discover patterns, anomalies, and relationships. Use when exploring data files, generating statistical summaries, checking data quality, or creating…
Generate testable hypotheses. Formulate from observations, design experiments, explore competing explanations, develop predictions, propose mechanisms, for scientific inq — from…
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and…
Systematic peer review toolkit. Evaluate methodology, statistics, design, reproducibility, ethics, figure integrity, reporting standards, for manuscript and grant review — from…
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Evaluate research rigor. Assess methodology, experimental design, statistical validity, biases, confounding, evidence quality (GRADE, Cochrane ROB), for critical analysis — from…
Create publication figures with matplotlib/seaborn/plotly. Multi-panel layouts, error bars, significance markers, colorblind-safe, export PDF/EPS/TIFF, for journal-ready…
Write scientific manuscripts. IMRAD structure, citations (APA/AMA/Vancouver), figures/tables, reporting guidelines (CONSORT/STROBE/PRISMA), abstracts, for research papers and…
Statistical analysis toolkit. Hypothesis tests (t-test, ANOVA, chi-square), regression, correlation, Bayesian stats, power analysis, assumption checks, APA reporting, for — from…
Statistical analysis toolkit. Hypothesis tests (t-test, ANOVA, chi-square), regression, correlation, Bayesian stats, power analysis, assumption checks, APA reporting, for — from…
PyTorch-native graph neural networks for molecules and proteins. Use when building custom GNN architectures for drug discovery, protein modeling, or knowledge graph reaso — from…
UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensio — from…
Scientific method for validating claims with pre-registration, power analysis, statistical rigor, and Bayesian methods.
Meta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-saf — from…
Meta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-saf — from…
This is the core skill for the deep research and writing tool—combining AI-driven deep research with well-formatted written outputs.
Core skill for the deep research and writing tool. Write scientific manuscripts in full paragraphs (never bullet points).
Core skill for the deep research and writing tool. Write scientific manuscripts in full paragraphs (never bullet points).
This is the core skill for the deep research and writing tool—combining AI-driven deep research with well-formatted written outputs.
Universal scientific thinking framework for rigorous inquiry across all domains - from engineering and data analysis to social sciences, humanities, arts, and human behav — from…
Universal scientific thinking framework for rigorous inquiry across all domains - from engineering and data analysis to social sciences, humanities, arts, and human behav — from…
Biological data toolkit. Sequence analysis, alignments, phylogenetic trees, diversity metrics (alpha/beta, UniFrac), ordination (PCoA), PERMANOVA, FASTA/Newick I/O, for m — from…
Geostatistical analysis with scikit-learn style API. Compute variograms, kriging interpolation, and spatial correlation analysis.
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality re — from…
SciPlot Academic 科研绘图技能（sciplot-academic 包配套 skill，本仓库默认绘图入口）。 当用户请求绘制科研/论文/竞赛图表（折线、散点、柱状、箱线、小提琴、热力、气泡热力、 边际分布、雨云、蜂群、山脊、六边形、哑铃、发散条形、甘特、打包气泡、雷达、3D 曲面/瀑布、 网络/3D 网络、维恩、密度、QQ、残差、PCA 等…
Best practices for SciPy scientific computing, optimization, signal processing, and statistical analysis in Python
Digital signal-processing utilities tuned for neuroscience workflows. `hilbert(x)` returns analytic signal; `psd(x, fs, ...)` and `band_powers(x, fs, bands)` compute spectral…
Miscellaneous SciTeX utilities — terminal single-keypress helpers for interactive scripts. Public API (2 symbols) — `wait_key()` (block until any key is pressed; returns the…
Generic SLURM dispatch + persistent reservations for the SciTeX ecosystem. One-shot `srun`/`sbatch`/`sync`/`poll`/`fetch_result` plus a `Reservation` primitive that lets you book…
Reproducibility helpers for scientific Python experiments — unified seeded random-state for `random`/`numpy`/`torch`/`tf`, experiment ID + timestamp generation, and deterministic…
Scientific-paper search, metadata enrichment, PDF download, and BibTeX library management for the SciTeX ecosystem.
`@session` decorator for reproducible experiment lifecycle. Wrap `def main(...)`; the decorator parses CLI args, loads `config/*.yaml`, configures matplotlib + logging, runs the…
Publication-ready statistical testing — 23 tests, effect sizes, power analysis, auto test selection, and MCP tools for AI agents.
Project scaffolding cloner + code snippet library for the SciTeX ecosystem. 6 templates (pip-project, minimal, cloud-module, research, singularity, paper) vendored in a single…
Use when after computing a scoring function over all possible genomic-metabolomic candidate pairs (e.g., all 2966 MIBiG-GNPS BGC-spectrum pairs), when you have a subset of known…