ReddRadar
Topic: scientific-computing
170 skills in this topic.
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gromacs
Use when working on biomolecular molecular dynamics with GROMACS, especially system setup, equilibration, production runs, trajectory analysis, or MM/PBSA-style post-processing.
ZimoLiao/scholaraio 332
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draw
Generate diagrams and vector graphics. Supports Mermaid (flowcharts, sequence diagrams, ER diagrams, Gantt charts, mind maps) via mermaid-py, and custom vector graphics (shapes, text, gradients, layers) via cli-anything-inkscape. Outputs PNG/SVG/PDF to workspace/. Use when the user wants to visualize workflows, architecture, data relationships, research timelines, concept maps, or create polished figures for papers.
ZimoLiao/scholaraio 332
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quantum-espresso
Use when working on first-principles materials calculations with Quantum ESPRESSO, especially SCF, band structures, DOS, phonons, electron-phonon coupling, Fermi surfaces, or charge-density analysis.
ZimoLiao/scholaraio 332
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enrich
Enrich paper metadata using LLM extraction. Extract table of contents (TOC), conclusions (L3), and backfill abstracts. Use when the user wants to extract conclusions, build TOC, or backfill missing abstracts. For citation count updates, see the /citations skill.
ZimoLiao/scholaraio 332
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import
Import papers from external reference managers (Endnote XML/RIS, Zotero Web API or local SQLite), or attach a PDF to an existing paper. Handles PDF matching, MinerU conversion, metadata enrichment, and index updates. Use when the user wants to import their existing library from Zotero, Endnote, attach/add a PDF to a paper, or supplement a paper with its PDF.
ZimoLiao/scholaraio 332
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scientific-runtime
Use when serving scientific CLI tasks through ScholarAIO, especially when the agent should prefer scholaraio toolref, handle partial coverage safely, and avoid turning user work into documentation maintenance.
ZimoLiao/scholaraio 332
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insights
Analyze research behavior data — search hot keywords, most-read papers, reading trends, and semantic neighbors you haven't read yet. Use when the user wants to understand their reading habits, discover overlooked papers, or review recent research activity.
ZimoLiao/scholaraio 332
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audit
Audit paper data quality in the knowledge base. Checks for missing fields, filename issues, DOI duplicates, title mismatches, and more. Supports LLM-based deep diagnosis for title mismatches and automated repair. Use when the user wants to check data quality, find problems, or fix metadata issues.
ZimoLiao/scholaraio 332
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search
Search academic papers in the local ScholarAIO knowledge base. Supports unified search (keyword + semantic fusion), keyword-only (FTS5), semantic-only (FAISS), author search, and federated search across main library, explore databases, and arXiv. Use when the user wants to find papers, look up literature, search by author, explore research topics, or search across multiple sources. For citation rankings and citation count updates, see the /citations skill.
ZimoLiao/scholaraio 332
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document
Generate and inspect Office documents (DOCX, PPTX, XLSX). Generate by writing Python scripts that call python-docx, python-pptx, and openpyxl APIs directly. Inspect with `scholaraio document inspect` to verify layout, content, and catch issues (overflow, missing elements). Use when the user wants to create Word reports, PowerPoint presentations, Excel data sheets, or inspect any Office document.
ZimoLiao/scholaraio 332
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neuropixels-analysis
Neuropixels neural recording analysis. Load SpikeGLX/OpenEphys data, preprocess, motion correction, Kilosort4 spike sorting, quality metrics, Allen/IBL curation, AI-assisted visual analysis, for Neuropixels 1.0/2.0 extracellular electrophysiology. Use when working with neural recordings, spike sorting, extracellular electrophysiology, or when the user mentions Neuropixels, SpikeGLX, Open Ephys, Kilosort, quality metrics, or unit curation.
K-Dense-AI/claude-scientific-skills 16,890
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adaptyv
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
K-Dense-AI/claude-scientific-skills 16,890
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histolab
Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.
K-Dense-AI/claude-scientific-skills 16,890
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statistical-analysis
Guided statistical analysis with test selection and reporting. Use when you need help choosing appropriate tests for your data, assumption checking, power analysis, and APA-formatted results. Best for academic research reporting, test selection guidance. For implementing specific models programmatically use statsmodels.
K-Dense-AI/claude-scientific-skills 16,890
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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, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.
K-Dense-AI/claude-scientific-skills 16,890
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bioservices
Unified Python interface to 40+ bioinformatics services. Use when querying multiple databases (UniProt, KEGG, ChEMBL, Reactome) in a single workflow with consistent API. Best for cross-database analysis, ID mapping across services. For quick single-database lookups use gget; for sequence/file manipulation use biopython.
K-Dense-AI/claude-scientific-skills 16,890
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cellxgene-census
Query the CELLxGENE Census (61M+ cells) programmatically. Use when you need expression data across tissues, diseases, or cell types from the largest curated single-cell atlas. Best for population-scale queries, reference atlas comparisons. For analyzing your own data use scanpy or scvi-tools.
K-Dense-AI/claude-scientific-skills 16,890
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pptx
Use this skill any time a .pptx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx file (even if the extracted content will be used elsewhere, like in an email or summary); editing, modifying, or updating existing presentations; combining or splitting slide files; working with templates, layouts, speaker notes, or comments. Trigger whenever the user mentions "deck," "slides," "presentation," or references a .pptx filename, regardless of what they plan to do with the content afterward. If a .pptx file needs to be opened, created, or touched, use this skill.
K-Dense-AI/claude-scientific-skills 16,890
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scholar-evaluation
Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and actionable feedback.
K-Dense-AI/claude-scientific-skills 16,890
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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 processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
K-Dense-AI/claude-scientific-skills 16,890
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database-lookup
Search 78 public scientific, biomedical, materials science, and economic databases via their REST APIs and return structured JSON results. Covers physics/astronomy (NASA, NIST, SDSS, SIMBAD, Exoplanet Archive), earth/environment (USGS, NOAA, EPA, OpenWeatherMap), chemistry/drugs (PubChem, ChEMBL, DrugBank, FDA, KEGG, DailyMed, ZINC, BindingDB), materials science (Materials Project, COD), biology/genomics (Reactome, BRENDA, UniProt, STRING, Ensembl, NCBI Gene, GEO, GTEx, PDB, AlphaFold, InterPro, ChEBI, BioGRID, Gene Ontology, QuickGO, NCBI Protein/Taxonomy, dbSNP, SRA, ENA, gnomAD, UCSC Genome, ENCODE, JASPAR, MouseMine, PRIDE, LINCS L1000, Human Protein Atlas, Human Cell Atlas, RummaGEO, Metabolomics Workbench, EMDB, Addgene), disease/clinical (COSMIC, Open Targets, ClinPGx, ClinicalTrials.gov, OMIM, ClinVar, GDC/TCGA, cBioPortal, DisGeNET, GWAS Catalog, Monarch, HPO), regulatory (FDA, USPTO, SEC EDGAR), economics/finance (FRED, BEA, BLS, Federal Reserve, World Bank, ECB, US Treasury, Alpha Vantage, Data Commons), and demographics (US Census, Eurostat, WHO). Use this skill whenever the user wants to look up compounds, drugs, proteins, genes, pathways, enzymes, gene expression, variants, clinical trials, patents, SEC filings, economic indicators, crystal structures, astronomical objects, earthquakes, weather, or any data from a public database API. Also trigger when the user mentions any database by name or asks about molecular properties, drug-target interactions, binding affinities, protein interactions, pathway membership, pharmacogenomics, economic time series, materials properties, commercially available compounds, virtual screening, compound purchasability, chemical libraries, building blocks, cancer genomics, somatic mutations, tumor mutation profiles, nucleotide sequences, genome assemblies, sequencing reads, ENA accessions, INSDC data, or wants to cross-reference entities across sources.
K-Dense-AI/claude-scientific-skills 16,890
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dnanexus-integration
DNAnexus cloud genomics platform. Build apps/applets, manage data (upload/download), dxpy Python SDK, run workflows, FASTQ/BAM/VCF, for genomics pipeline development and execution.
K-Dense-AI/claude-scientific-skills 16,890
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diffdock
Diffusion-based molecular docking. Predict protein-ligand binding poses from PDB/SMILES, confidence scores, virtual screening, for structure-based drug design. Not for affinity prediction.
K-Dense-AI/claude-scientific-skills 16,890
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pdf
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, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.
K-Dense-AI/claude-scientific-skills 16,890