Claude Skills
The open format is called Agent Skills and works in Claude Code, Codex, Cursor and other agents — most people know it as Claude Skills.
Every Agent Skill we could find on GitHub, deduplicated by content. 86 696 files from 2 113 authors, of which 68 413 are unique — the rest is the same skill repackaged into someone else's repository. For each one: what it weighs in tokens, whether it ships runnable scripts, and which MCP servers it needs.
Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), drug sensitivity data, and gene effect profiles. Use when identifying cancer-specific genetic vulnerabilities, finding synthetic lethal interactions, checking whether a gene is essential in given cell lines, or validating oncology drug targets. Part of the AlterLab Academic Skills suite.
Access and analyze drug information from the DrugBank database — drug properties, interactions, targets, pathways, chemical structures, and pharmacology data. Use when working with pharmaceutical data, drug discovery research, drug-drug interaction analysis, target identification, chemical similarity searches, ADMET predictions, or any task needing detailed drug and drug-target records from DrugBank. Part of the AlterLab Academic Skills suite.
Access the European Nucleotide Archive (ENA) via its API and FTP to retrieve DNA/RNA sequences, raw sequencing reads (FASTQ), and genome assemblies by accession, with support for multiple formats. Use when downloading reads or sequences for a study, run, or sample accession, or when sourcing nucleotide data for genomics and bioinformatics pipelines. Part of the AlterLab Academic Skills suite.
Query the openFDA API for drugs, medical devices, adverse event reports, recalls, regulatory submissions (510k, PMA), and substance identification (UNII). Use when searching FDA safety data, pharmacovigilance and adverse-event signals, device clearances, drug labels, or recall records for regulatory data analysis and safety research. Part of the AlterLab Academic Skills suite.
Query the Ensembl genome database REST API across 250+ species for gene lookups, sequence retrieval, variant analysis, comparative genomics, orthologs, and Variant Effect Predictor (VEP) annotations. Use when mapping gene IDs or coordinates, fetching genomic sequence, finding orthologs across species, or predicting variant consequences for genomic research. Part of the AlterLab Academic Skills suite.
Query NCBI Gene via the E-utilities and Datasets APIs, searching by gene symbol or Gene ID and retrieving gene information (RefSeqs, GO terms, genomic locations, associated phenotypes) including batch lookups. Use when resolving gene symbols to IDs, annotating gene lists, or pulling functional and positional gene metadata for downstream analysis. Part of the AlterLab Academic Skills suite.
Query the GTEx (Genotype-Tissue Expression) portal v2 REST API for tissue-specific gene expression (median TPM across 54 human tissues), expression QTLs (eQTLs), and splicing QTLs (sQTLs). Use when checking which tissues express a gene, finding which gene a non-coding/GWAS variant regulates via eQTLs, or interpreting variant regulatory effects across tissues. NOT for curated trait-variant associations (use alterlab-gwas), population allele frequencies or variant constraint (use alterlab-gnomad), or gene/transcript structure and ID mapping (use alterlab-ensembl). Part of the AlterLab Academic Skills suite.
Query gnomAD (Genome Aggregation Database) for population allele frequencies and gene constraint scores (pLI, LOEUF) reflecting loss-of-function intolerance. Use when checking how common a variant is across populations, filtering rare-disease candidate variants, assessing variant pathogenicity, or identifying loss-of-function intolerant genes. Part of the AlterLab Academic Skills suite.
Access NCBI GEO (Gene Expression Omnibus) for gene expression and functional genomics data — search and download microarray and RNA-seq datasets by GSE, GSM, GPL, or GDS accession and retrieve SOFT, MINiML, and series matrix files. Use when locating public expression datasets, fetching processed expression matrices, downloading a study's supplementary files, or sourcing per-study transcriptomics data for differential-expression analysis. For raw FASTQ sequencing reads by SRA/ENA run accession use alterlab-ena; for reference tissue-expression baselines (median TPM across human tissues) use alterlab-gtex; for cancer cohort somatic mutations and copy-number use alterlab-cbioportal. Part of the AlterLab Academic Skills suite.
Access the Human Metabolome Database (HMDB, 220K+ metabolites), searching by name, HMDB ID, or structure to retrieve chemical properties, biomarker data, NMR/MS reference spectra, and associated pathways. Use when identifying a human metabolite, looking up its biomarker or disease associations, matching NMR/MS spectra, or running metabolomics annotation. Part of the AlterLab Academic Skills suite.
Query the NHGRI-EBI GWAS Catalog REST API for SNP-trait associations, retrieving variants by rs ID, disease/trait, or gene along with p-values and summary statistics. Use when investigating genome-wide association study hits, mapping a SNP or rsID to traits, building polygenic risk scores, or doing genetic epidemiology lookups. Part of the AlterLab Academic Skills suite.
Query the EMBL-EBI InterPro REST API for protein family, domain, and functional-site annotations integrated from member databases (Pfam, PANTHER, PRINTS, SMART, SUPERFAMILY, CDD, ProSite, NCBIfam, and others). Use when predicting protein function, analyzing or comparing domain architecture, classifying a protein by family or homologous superfamily, resolving a Pfam/InterPro accession, or mapping a protein's signatures to GO terms. Not for raw UniProt entry/FASTA retrieval or AlphaFold 3D structures. Part of the AlterLab Academic Skills suite.
Query and download public cancer imaging data from the NCI Imaging Data Commons (IDC) using the idc-index Python package, filtering by metadata, visualizing in-browser, and checking licenses, with no authentication required. Use when obtaining large-scale radiology (CT, MR, PET) or digital pathology DICOM datasets for AI/ML training or cancer imaging research. Part of the AlterLab Academic Skills suite.
Query JASPAR for transcription factor binding site (TFBS) profiles (PWMs/PFMs), searching by TF name, species, or class, scanning DNA sequences for binding sites, and comparing matrices. Use when doing motif analysis, regulatory genomics, transcription factor binding prediction, or interpreting regulatory/non-coding GWAS variants. Part of the AlterLab Academic Skills suite.
Access the NIH Metabolomics Workbench via its REST API (4,200+ studies), querying metabolites, RefMet standardized nomenclature, MS/NMR data, m/z mass searches, and study metadata. Use when retrieving public metabolomics study data, standardizing metabolite names with RefMet, running m/z lookups, or doing biomarker discovery. Part of the AlterLab Academic Skills suite.
Provide direct REST API access to KEGG (academic use only) for pathway analysis, gene-to-pathway and compound-to-pathway mapping, metabolic reactions, KEGG Orthology (KO), drug-drug interactions, and ID conversion. Use when querying KEGG pathways, mapping genes/compounds to metabolic maps, or running KEGG pathway enrichment via raw HTTP/REST; for protein-protein interaction networks prefer alterlab-string-db, for protein sequences and annotations prefer alterlab-uniprot, and for Python workflows spanning many databases prefer bioservices instead. Part of the AlterLab Academic Skills suite.
Query the Monarch Initiative knowledge graph for disease-gene-phenotype associations across species, integrating OMIM, ORPHANET, HPO, ClinVar, and model organism databases. Use when discovering rare disease genes, mapping phenotypes to genes, modeling disease across species, or looking up HPO terms. Part of the AlterLab Academic Skills suite.
Query and analyze scholarly literature using the OpenAlex API across 240M+ works, retrieving papers, authors, institutions, citations, and open access status. Use when searching academic papers, tracking citations, finding works by author or institution, analyzing research trends, discovering open access publications, or running bibliometric analysis. Part of the AlterLab Academic Skills suite.
Query the Open Targets Platform GraphQL API for target-disease associations, tractability and safety data, genetics/omics evidence, and known drugs. Use when identifying or prioritizing therapeutic drug targets, assessing target druggability/safety, or gathering target-disease evidence for drug discovery. Part of the AlterLab Academic Skills suite.
Access the RCSB Protein Data Bank (PDB) for EXPERIMENTALLY determined 3D structures (X-ray, cryo-EM, NMR) of proteins and nucleic acids — searching by text, sequence, or structure similarity and downloading coordinates in PDB/mmCIF format with metadata. Use when retrieving a structure by PDB ID, running sequence or structure similarity searches, or obtaining experimental coordinates for structural biology and drug discovery; for AI-PREDICTED structures of proteins lacking experimental data prefer alterlab-alphafold-db, and for protein sequences, annotations, or accession ID mapping prefer alterlab-uniprot instead. Part of the AlterLab Academic Skills suite.
Query PubChem via the PUG-REST API and PubChemPy across 110M+ compounds, searching by name, CID, or SMILES and retrieving molecular properties, bioactivity, and similarity/substructure matches. Use when looking up a chemical compound, converting names/SMILES to CIDs, fetching physicochemical properties, or running cheminformatics structure searches. Part of the AlterLab Academic Skills suite.
Provide direct REST API access to PubMed via the NCBI E-utilities API, supporting advanced Boolean/MeSH queries, batch processing, and citation management. Use when searching biomedical literature by MeSH terms, retrieving abstracts or PMIDs in bulk, or scripting custom PubMed queries over raw HTTP/REST — for Python workflows prefer biopython (Bio.Entrez) instead, use this for direct REST work or custom API implementations. Part of the AlterLab Academic Skills suite.
Query the Reactome REST API for pathway analysis, over-representation/enrichment, gene-to-pathway mapping, disease pathways, molecular interactions, and expression analysis. Use when running pathway enrichment on a gene list, mapping genes to curated biological pathways, or exploring disease pathways for systems biology studies. Part of the AlterLab Academic Skills suite.
Query the STRING API for protein-protein interactions (59M proteins, 20B interactions across 5000+ species), building interaction networks, discovering functional partners, and running GO/KEGG/Pfam enrichment on protein lists. Use when constructing a protein-protein interaction network, expanding from seed proteins to functional partners, or running PPI-based enrichment for systems biology; for curated metabolic pathway maps and reactions prefer alterlab-kegg, and for protein sequences, annotations, or accession ID mapping prefer alterlab-uniprot instead. Part of the AlterLab Academic Skills suite.
Provide direct REST API access to UniProt (Swiss-Prot/TrEMBL) for protein sequence searches, FASTA retrieval, functional annotations (GO terms, domains), and cross-database ID mapping. Use when looking up a protein entry, fetching a protein FASTA sequence, or mapping accessions between databases over raw HTTP/REST; for EXPERIMENTAL 3D structures prefer alterlab-pdb, for AI-PREDICTED 3D structures prefer alterlab-alphafold-db, for protein-protein interaction networks prefer alterlab-string-db, and for Python workflows spanning many databases prefer bioservices instead. Part of the AlterLab Academic Skills suite.
Access the ZINC database of 230M+ commercially available (purchasable) compounds, searching by ZINC ID or SMILES, running similarity searches, and downloading 3D-ready structures. Use when assembling a compound library for virtual screening, finding purchasable analogs, or obtaining docking-ready 3D structures for drug discovery. Part of the AlterLab Academic Skills suite.
Access USPTO APIs for patent and trademark searches, examination history (PEDS), assignments, citations, office actions, and trademark status (TSDR). Use when searching patents or trademarks, conducting prior art searches, retrieving patent examination or assignment records, or doing intellectual property (IP) analysis. Part of the AlterLab Academic Skills suite.
Convert files and Office documents to clean, LLM-friendly Markdown with Microsoft MarkItDown (markitdown CLI/Python), supporting PDF, DOCX, PPTX, XLSX, images (EXIF + OCR), audio (transcription), HTML, CSV, JSON, XML, ZIP archives, EPUB e-books, and YouTube transcript URLs, with optional AI image descriptions. Use when converting a document, PDF, slide deck, spreadsheet, scanned image, audio file, web page, or e-book into Markdown text for ingestion or LLM processing, extracting text via OCR, transcribing audio, or batch-converting mixed file formats to token-efficient Markdown. Part of the AlterLab Academic Skills suite.
Run Open Notebook, a self-hosted open-source alternative to Google NotebookLM with a full REST API, for AI-powered research and document analysis. Use when organizing research materials into notebooks, ingesting diverse content sources (PDFs, videos, audio, web pages, Office documents), generating AI-powered notes and summaries, creating multi-speaker podcasts from research, chatting with documents using context-aware AI, searching across materials with full-text and vector search, or running custom content transformations. Supports 18+ AI providers including OpenAI, Anthropic, Google, Ollama, LM Studio, Groq, and Mistral with complete data privacy through self-hosting. For a one-shot file-to-Markdown conversion (no notebook, chat, or search), use alterlab-markitdown instead. Part of the AlterLab Academic Skills suite.
Explore a single PDF in depth — parse it once, then answer questions across its sections, figures, tables, and appendices — comparing methods across sections, extracting every instance of a pattern within the document, and reading values off its charts and tables. Use when interrogating one paper or report end-to-end, pulling every occurrence of something inside a document, or reading data from a figure/table in a PDF, serving the literature-review and paper-review pipeline. To build a comparison table across MANY papers prefer alterlab-pdf-extract; to simply convert a PDF to Markdown prefer alterlab-markitdown; for reference/citation management prefer alterlab-pyzotero. Part of the AlterLab Academic Skills suite.
Submits and tracks protein-testing experiments on the Adaptyv Bio Foundry cloud lab (wet-lab validation), and optimizes protein sequences before submission with computational tools (NetSolP, SoluProt, SolubleMPNN, ESM). Use when designing proteins that need wet-lab validation - binding/affinity screening, expression testing, thermostability, or fluorescence assays - or when submitting experiments to the Foundry API, browsing the target catalog, tracking experiment status, retrieving results, or pre-screening sequences for solubility/expression. Triggers on "Adaptyv", "Foundry API", "cloud lab", "biolayer interferometry / BLI", "wet-lab validation". Part of the AlterLab Academic Skills suite.
Runs time series machine learning with the aeon library — classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search via scikit-learn compatible APIs. Use when working with temporal data, sequential patterns, or time-indexed observations (univariate or multivariate) that need specialized algorithms beyond standard ML approaches. Part of the AlterLab Academic Skills suite.
Processes astronomy and astrophysics data with the Astropy Python library — celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, and world coordinate systems (WCS). Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or general astronomical data analysis. Part of the AlterLab Academic Skills suite.
Builds, simulates, and runs quantum circuits with Cirq, Google Quantum AI's framework for NISQ hardware, noise-aware low-level circuit design, and noise characterization. Use when targeting Google Quantum AI processors (Sycamore/Weber), designing noise-aware NISQ circuits, or running characterization experiments (randomized benchmarking, XEB). For IBM Quantum hardware and Qiskit Runtime prefer alterlab-qiskit; for gradient-trained quantum ML and hybrid quantum-classical models prefer alterlab-pennylane; for open-system Lindblad/master-equation dynamics prefer alterlab-qutip. Part of the AlterLab Academic Skills suite.
Applies computational methods to humanities research — text mining and NLP (LDA/BERTopic topic modeling, sentiment, named entity recognition with spaCy/NLTK), corpus linguistics (concordance, collocation, keyness), digital archives (Dublin Core, TEI XML), GIS for history, network analysis, stylometry and authorship attribution, OCR (Tesseract, Kraken, Transkribus), and data visualization (Gephi, Palladio). Use when distant-reading a literary corpus, mapping historical events or trade networks, attributing disputed authorship, digitizing historical documents, or building digital scholarly editions. Part of the AlterLab Academic Skills suite.
Runs computational fluid dynamics simulations with the FluidSim Python framework using pseudospectral FFT methods, with HPC support and output analysis. Use when simulating Navier-Stokes equations (2D/3D), shallow water equations, or stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Part of the AlterLab Academic Skills suite.
Machine learning on genomic interval data (BED files) with the geniml Python package — region embeddings (Region2Vec), joint region+metadata embeddings (BEDspace/StarSpace), single-cell ATAC-seq embeddings (scEmbed), consensus peak sets / universes (build-universe), tokenization, BEDshift randomization, and BBClient/BEDbase caching. Use when training or using region/cell embeddings, clustering scATAC-seq, building a tokenization universe from BED collections, or any ML/feature-learning task over genomic regions. NOT for plain interval arithmetic (overlap/intersect/merge counts) — that is gtars, not geniml. Part of the AlterLab Academic Skills suite.
Reads, writes, and analyzes geospatial vector data with the GeoPandas Python library (shapefiles, GeoJSON, GeoPackage), with PostGIS support and integration with matplotlib, folium, and cartopy. Use for spatial analysis and geometric operations — buffer analysis, spatial joins and overlays between datasets, dissolving boundaries, clipping, calculating areas and distances, reprojecting coordinate systems, choropleth mapping, or converting between vector file formats. This is for tabular vector data; for raster/satellite/DEM work, spectral indices (NDVI), or spatial ML on earth observation prefer the geomaster skill. Part of the AlterLab Academic Skills suite.
Runs high-performance genomic interval analysis with gtars (databio), a Rust toolkit with Python bindings — the performance-critical backend for the geniml ML library. Use when computing overlaps/jaccard/coverage between BED region sets, indexing intervals with IGD, generating uniwig accumulation/coverage tracks, tokenizing genomic regions for ML, splitting single-cell fragments into pseudobulks, or computing GA4GH refget sequence digests. NOT for training region embeddings (use alterlab-geniml) or non-genomic spatial joins (use alterlab-geopandas). Part of the AlterLab Academic Skills suite.
Covers geospatial science across remote sensing, GIS, spatial analysis, and machine learning for earth observation — satellite imagery processing (Sentinel, Landsat, MODIS, SAR, hyperspectral), raster and DEM operations, spectral indices (NDVI/EVI/NDWI), spatial statistics, point cloud processing, network analysis, and cloud-native workflows (STAC, COG, Planetary Computer), with examples across Python, R, Julia, JavaScript, C++, Java, Go, and Rust. Use for remote sensing workflows, satellite/raster image classification, terrain/slope/hillshade analysis, spatial ML on earth-observation data, hydrological modeling, marine spatial analysis, or atmospheric science. For pure tabular vector work with no raster/EO aspect (plain GeoPandas sjoin, buffer, overlay, dissolve, choropleths) prefer the geopandas skill; for celestial-sphere astronomy coordinates (ICRS/galactic, FITS, WCS) prefer the astropy skill. Part of the AlterLab Academic Skills suite.
Runs automated LLM-driven hypothesis generation and testing on tabular datasets with HypoGeniC, combining literature insights with data-driven testing. Use when systematically exploring hypotheses about patterns in empirical data (for example deception detection or content analysis). For manual hypothesis formulation use alterlab-hypothesis-gen; for open-ended creative ideation use alterlab-scientific-brainstorm. Part of the AlterLab Academic Skills suite.
Runs Python code in the cloud with Modal — serverless containers, on-demand GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that need GPU acceleration or dynamic scaling. Part of the AlterLab Academic Skills suite.
Trains and differentiates quantum circuits with PennyLane, a hardware-agnostic quantum machine-learning framework with automatic differentiation and PyTorch/JAX/TensorFlow integration. Use when training quantum circuits via gradients (parameter-shift, backprop, adjoint), building hybrid quantum-classical models or quantum neural networks, or running differentiable variational algorithms (VQE, QAOA). For IBM Quantum hardware and Qiskit Runtime prefer alterlab-qiskit; for Google Quantum AI or NISQ circuits prefer alterlab-cirq; for open-system Lindblad/master-equation dynamics prefer alterlab-qutip. Part of the AlterLab Academic Skills suite.
Analyzes and manipulates materials with the pymatgen toolkit — crystal structures and molecules, phase diagrams and thermodynamic stability, electronic structure (band structures, DOS), surfaces and interfaces, and Materials Project database access. Use when working with crystal structures in materials science, converting between structure formats (CIF, POSCAR, XYZ), analyzing symmetry or space groups, computing phase diagrams, querying the Materials Project API, or handling VASP, Gaussian, or Quantum ESPRESSO output. Part of the AlterLab Academic Skills suite.
Builds, transpiles, and runs quantum circuits with Qiskit, IBM's quantum computing framework, including Qiskit Runtime primitives (Sampler/Estimator), circuit transpilation, and error mitigation on IBM Quantum hardware. Use when targeting IBM Quantum backends, transpiling circuits, running Runtime sessions or batches, or applying resilience/error mitigation. For Google Quantum AI hardware and NISQ circuits prefer alterlab-cirq; for gradient-trained quantum ML and hybrid quantum-classical models prefer alterlab-pennylane; for open-system Lindblad/master-equation dynamics prefer alterlab-qutip. Part of the AlterLab Academic Skills suite.
Guides advanced social science research methods — discourse analysis (Fairclough CDA, Gee), conversation analysis, quantitative content analysis, Qualitative Comparative Analysis (QCA), process tracing, archival research, participatory/community-based research (PAR, CBPR), Delphi and Q methodology, social network analysis (SNA), bibliometrics and scientometrics, systematic mapping reviews, and program/policy evaluation. Use when designing or conducting any of these studies — choosing a specialized method, building a coding scheme, establishing causal mechanisms in case studies, mapping relational or subjective data, or applying an evaluation framework. For interpretive/qualitative coding (thematic analysis, grounded theory, IPA, ethnography, qualitative content analysis) use alterlab-qualitative-methods; for combining qual+quant strands use alterlab-mixed-methods. Part of the AlterLab Academic Skills suite.
Simulates open quantum systems with QuTiP, the Quantum Toolbox in Python, solving Lindblad master equations (mesolve), Monte Carlo trajectories (mcsolve), and unitary dynamics (sesolve). Use when studying master-equation or Lindblad dynamics, decoherence, dissipation, quantum optics, cavity QED, or open-system time evolution. NOT for circuit-based quantum computing or hardware execution — for IBM Quantum circuits prefer alterlab-qiskit, for Google Quantum AI or NISQ circuits prefer alterlab-cirq, and for gradient-trained quantum ML prefer alterlab-pennylane. Part of the AlterLab Academic Skills suite.
Dispatch long-running GPU/CPU jobs to remote compute with a provider-agnostic submit → poll → harvest pattern across SLURM/HPC (sbatch, squeue, sacct) and managed APIs (Modal, RunPod, GCP Batch / Vertex AI). Use when submitting a batch job to a cluster, polling job status, retrieving result artifacts from a scheduler or cloud GPU provider, or writing a portable job-submission wrapper; the foundation-model skills (alterlab-alphafold, alterlab-boltz, alterlab-rfdiffusion, and siblings) dispatch their GPU work through this pattern. For Modal-specific serverless container deployment and autoscaling prefer alterlab-modal instead. Part of the AlterLab Academic Skills suite.
Scaffolds program-level Assurance-of-Learning (AoL) documentation for AACSB (2020 Standard 5) and ABET (Criterion 3 Student Outcomes, Criterion 4 Continuous Improvement) accreditation — program learning outcomes / competency goals, curriculum-to-outcome mapping matrices, direct- and indirect-assessment plans, rubric design, and closing-the-loop continuous-improvement narratives — and validates the structure of an outcome-mapping matrix with scripts/aol_matrix.py. Use when the user needs AACSB or ABET assurance-of-learning material, a program-learning-outcomes set, a curriculum/outcome map or coverage matrix, a direct/indirect assessment plan, a closing-the-loop report, or accreditation self-study text. For single-course design or course rubrics prefer alterlab-teaching-design; for post-award grant reports prefer alterlab-grant-reporting. Part of the AlterLab Academic Skills suite.
Drafts post-award grant deliverables across funder formats — NIH RPPR (Annual/Interim/Final via eRA Commons), NSF annual/final project reports and the public Project Outcomes Report (Research.gov), and Horizon Europe / ERC periodic and final reports (technical Part A/B + financial statements on the EU Funding & Tenders Portal) — plus milestone and deliverable tracking, budget-vs-actual variance narratives, no-cost-extension and rebudgeting justifications, and effort/closeout reporting. Computes report due dates from the award period with scripts/report_deadlines.py. Use when the user needs a grant progress or final report, post-award reporting, an RPPR, a periodic report, a no-cost-extension request, milestone tracking, or a budget-variance narrative. For writing new proposals prefer alterlab-research-grants; for TÜBİTAK proposals prefer alterlab-tubitak-proposal. Part of the AlterLab Academic Skills suite.
Drives preprint deposition across servers (arXiv, bioRxiv, medRxiv, SSRN, OSF Preprints): picks the right server by field, prepares submission metadata, sets the license (arXiv offers CC BY/BY-SA/BY-NC-SA/BY-NC-ND 4.0, the arXiv non-exclusive license, or CC0; bioRxiv/medRxiv offer CC BY/BY-NC/BY-ND/BY-NC-ND/CC0 or No-reuse), maps arXiv category taxonomy, handles immutable versioning and preprint DOIs, checks a journal's preprint/self-archiving policy via the Sherpa Romeo v2 API, and links the posted preprint to the published article. Reuses alterlab-arxiv and alterlab-biorxiv for metadata and alterlab-open-science for data-repository choice. Use when depositing a preprint, choosing a preprint server, preparing an arXiv or bioRxiv submission, setting a preprint license, or checking journal preprint policy; for Zenodo/Dryad/Figshare data deposition prefer alterlab-open-science, for TÜBİTAK Aperta prefer alterlab-aperta. Part of the AlterLab Academic Skills suite.
Drafts evidence-anchored academic reference and recommendation letters across types — graduate admission, faculty hiring, tenure/promotion external review, fellowship, and award nomination — from a structured prompt of candidate accomplishments, role context, evaluator relationship, and audience, calibrating specificity and register to the letter type and running a no-fabrication guard that flags unsupported superlatives, unanchored rankings, and claims with no evidence in the supplied dossier. Ships scripts/letter_scaffold.py to emit a typed section skeleton and scripts/claim_guard.py to lint a draft for evidence-free assertions. Use when the request is to write a recommendation or reference letter for a student or colleague, a tenure or promotion external-review letter, a fellowship or award nomination, or to check a letter draft for unsupported claims. For a candidate writing their own CV, research statement, or career narrative prefer alterlab-academic-career. Part of the AlterLab Academic Skills suite.
Designs validated research data-capture instruments and aligns them to CDISC submission standards. Builds REDCap projects from a requirements spec: instrument and field design, the 18-column data dictionary (Variable/Field Name, Form Name, Field Type, Choices, Branching Logic, Text Validation, Identifier?), field validation (date_ymd, integer, number, email, phone), branching/show-field logic, longitudinal events and survey settings, and lints a data dictionary for common errors. Maps a study to CDISC: CDASH collection fields, SDTM domain mapping (DM, AE, VS, LB, EX, CM, MH across Interventions/Events/Findings classes), and NCI-EVS controlled terminology. Use when the user wants to build a REDCap project, write or lint a data dictionary, set up branching logic or validation, or map a study to CDISC SDTM/CDASH/CDISC CT. For LabArchives ELN bridging use alterlab-labarchive; for Likert/sampling/reliability use alterlab-survey-design. Part of the AlterLab Academic Skills suite.
Drafts course-level generative-AI use policies and syllabus statements: assigns each graded task a permitted/restricted/prohibited tier (modeled on Cornell's prohibit/allow-with-attribution/encourage framework), writes the disclosure clause with a verbatim APA (OpenAI, 2023) or MLA Works Cited citation template for ChatGPT, and adds assessment-integrity, accessibility, and equity language bound to the institution's own academic-integrity code. Ships scripts/policy_builder.py to emit a paste-ready statement and scripts/policy_lint.py to flag a vague or self-contradicting draft. Use when the request mentions a syllabus AI policy, a course statement on ChatGPT or generative AI, an academic-integrity clause for AI tools, an AI-disclosure rule, or per-assignment permitted/prohibited AI tiers. For full course/backward design, syllabus, or rubrics use alterlab-teaching-design; for human-subjects AI-tool ethics use alterlab-research-ethics. Part of the AlterLab Academic Skills suite.
Accesses real-time and historical stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, and 50+ technical indicators via the Alpha Vantage API (requires a free API key from alphavantage.co). Use when fetching stock prices (OHLCV), company fundamentals (income statement, balance sheet, cash flow), earnings, options data, market news/sentiment, insider transactions, GDP, CPI, treasury yields, gold/silver/oil prices, Bitcoin/crypto prices, forex exchange rates, or calculating technical indicators (SMA, EMA, MACD, RSI, Bollinger Bands). Part of the AlterLab Academic Skills suite.
Runs Denario (AstroPilot-AI), a multiagent AI system for scientific research assistance that automates end-to-end research workflows from a described dataset through idea, methodology, computational results, and a publication-ready LaTeX paper. Built on AG2 + LangGraph with a cmbagent analysis backend. Use when driving the Denario pipeline (Denario.get_idea/get_method/get_results/get_paper), generating research ideas from a dataset description, auto-developing methodology, executing analysis agents, or emitting a journal-formatted (APS/AAS/JHEP/ICML/NeurIPS/PASJ) LaTeX manuscript. Part of the AlterLab Academic Skills suite.
Accesses, analyzes, and extracts data from SEC EDGAR filings using the edgartools Python library. Use when working with SEC filings, financial statements (income statement, balance sheet, cash flow), XBRL financial data, insider trading (Form 4), institutional holdings (13F), company financials, annual/quarterly reports (10-K, 10-Q), proxy statements (DEF 14A), 8-K current events, company screening by ticker/CIK/industry, multi-period financial analysis, or any SEC regulatory filings. Part of the AlterLab Academic Skills suite.
Queries the FRED (Federal Reserve Economic Data) API for 800,000+ economic time series from 100+ sources, covering GDP, unemployment, inflation, interest rates, exchange rates, housing, and regional data. Use for macroeconomic analysis, financial research, policy studies, economic forecasting, fetching U.S. or international economic indicators by FRED series ID, and academic research requiring historical economic time series. Part of the AlterLab Academic Skills suite.
Queries the OFR (Office of Financial Research) Hedge Fund Monitor API for time series on hedge fund size, leverage, counterparties, liquidity, complexity, and risk management, including SEC Form PF aggregated statistics, CFTC Traders in Financial Futures, FICC Sponsored Repo volumes, and FRB SCOOS dealer financing terms (no API key or registration required). Use when working with hedge fund data, systemic risk monitoring, financial stability research, hedge fund leverage or leverage ratios, counterparty concentration, Form PF statistics, repo market data, or OFR financial research data. Part of the AlterLab Academic Skills suite.
Generates comprehensive market research reports (50+ pages) in the style of top consulting firms (McKinsey, BCG, Gartner), with professional LaTeX formatting, extensive visuals via scientific-schematics and generate-image, data gathering through research-lookup, and multi-framework strategic analysis (Porter Five Forces, PESTLE, SWOT, TAM/SAM/SOM, BCG Matrix). Use when producing a market analysis, competitive landscape, industry report, market-sizing study, or consulting-style strategic deliverable. NOT for a single focused, source-cited research question with no report/frameworks (use alterlab-deep-research) or for pulling raw financial data points from an API (use alterlab-alpha-vantage). Part of the AlterLab Academic Skills suite.
Claude Skills — questions
Answers built from the skills we actually parsed.