AlterLab Academic Skills

Builds plots with the matplotlib Python library (pyplot and the object-oriented Figure/Axes API) for full low-level customization, exporting to PNG/PDF/SVG. Use when fine-grained control over individual plot elements is needed — custom line/scatter/bar/histogram/heatmap/contour/box/violin/3D plots, rcParams and style-sheet tuning, or GridSpec subplot layouts inside a scientific Python workflow. Does NOT cover opinionated journal-ready multi-panel figure workflows (Nature/Science/Cell formatting, colorblind-safe palettes, significance annotations); for those prefer alterlab-scientific-viz instead. Part of the AlterLab Academic Skills suite.

Manipulate, annotate, and render phylogenetic trees programmatically with the ETE Toolkit (ete3) — parse and edit Newick/NHX, detect duplication/speciation events, infer orthology and paralogy, query NCBI taxonomy, and export PDF/SVG figures. Use when traversing or reformatting tree files, doing phylogenomic comparative analysis, or producing publication tree graphics in Python. Part of the AlterLab Academic Skills suite.

Design protein sequences around bound ligands, metals, and nucleic acids with LigandMPNN (Dauparas 2023) — inverse folding that conditions on non-protein context, so binding-pocket and metal-site residues are chosen to fit the actual ligand. Use when designing a small-molecule or metal binding pocket, redesigning residues that contact a ligand/ion/nucleic acid, or doing enzyme active-site design where the substrate matters. For backbone sequence design with NO ligand/metal context prefer alterlab-proteinmpnn; to GENERATE a backbone or scaffold a functional site prefer alterlab-rfdiffusion; to validate a design by refolding prefer alterlab-alphafold; to co-fold or dock the ligand prefer alterlab-boltz or alterlab-diffdock. Part of the AlterLab Academic Skills suite.

Analyze biological data with scikit-bio — sequence analysis and alignments, phylogenetic trees, alpha/beta diversity metrics (including UniFrac), ordination (PCoA), PERMANOVA statistics, and FASTA/Newick I/O. Use for microbiome and community-ecology analysis — computing diversity, distance matrices, and ordination from feature tables. Part of the AlterLab Academic Skills suite.

Train deep generative models for single-cell omics with scvi-tools — probabilistic batch correction and integration (scVI), reference-mapping transfer learning (scArches), differential expression with uncertainty, and multimodal models (totalVI for CITE-seq, MultiVI for multiome). Use when correcting batch effects, integrating multimodal data, or doing advanced probabilistic single-cell modeling — for standard analysis pipelines use scanpy. Part of the AlterLab Academic Skills suite.

Builds PyTorch-native graph neural networks with TorchDrug for molecules and proteins, exposing custom GNN architectures, task/dataset abstractions, molecular generation, retrosynthesis planning, and knowledge-graph reasoning. Use when developing custom graph model layers, predicting protein properties from sequence or structure, or building retrosynthesis and drug-repurposing pipelines; for ready-made featurizers, MoleculeNet benchmarks, and pre-trained models with less code prefer alterlab-deepchem. Part of the AlterLab Academic Skills suite.

Reads, writes, and manipulates DICOM (Digital Imaging and Communications in Medicine) medical imaging files with the pydicom Python library. Use when reading/writing/modifying DICOM data, extracting pixel data from CT, MRI, X-ray, or ultrasound images, anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM to other formats, handling compressed DICOM, or processing medical imaging datasets for PACS systems, radiology workflows, and healthcare imaging applications. Part of the AlterLab Academic Skills suite.

Classical machine learning in Python with scikit-learn — algorithms, preprocessing, pipelines, and best-practice reference documentation. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, feature preprocessing, or building ML pipelines. Part of the AlterLab Academic Skills suite.

Pre-trained transformer models with Hugging Face Transformers for NLP, computer vision, audio, and multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, or fine-tuning transformer models on custom datasets. 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.

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.

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.

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.

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.

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.

Develops and runs genomics pipelines on the DNAnexus cloud platform using the dxpy Python SDK and dx CLI — build apps/applets, write dxapp.json, upload/download data, and execute jobs/workflows over FASTQ/BAM/VCF files. Use when building or running a DNAnexus app, applet, or workflow, writing dxapp.json, using dx-app-wizard or dx build, calling dxpy (find_data_objects, DXApplet.run, upload_local_file), or uploading/downloading sequencing data on DNAnexus. For LatchBio (Latch SDK @workflow/@task, LatchFile) use alterlab-latchbio instead; for Benchling LIMS use alterlab-benchling. Part of the AlterLab Academic Skills suite.

Builds and deploys bioinformatics pipelines on the LatchBio platform using the Latch SDK — author workflows with @workflow/@task decorators, handle LatchFile/LatchDir I/O, register serverless workflows, configure CPU/GPU task resources, organize data in the Latch Registry, and wrap Nextflow/Snakemake pipelines. Use when developing or deploying a Latch SDK workflow, sizing task resources, working with the Registry, or porting a Nextflow/Snakemake bioinformatics pipeline onto LatchBio. Not for DNAnexus (dxpy/dx CLI) or generic Flyte. Part of the AlterLab Academic Skills suite.

Run AI web searches with real-time, citation-grounded answers using Perplexity Sonar models (sonar, sonar-pro, sonar-pro-search agentic search, sonar-reasoning, sonar-reasoning-pro) via LiteLLM and a single OpenRouter API key. Use when searching for current information or recent scientific literature, getting answers grounded in cited web sources, verifying a claim against current evidence, or reaching information beyond the model's training cutoff. Requires an OpenRouter API key. This is the direct single-backend Perplexity tool: for automatic routing between Perplexity and other backends use alterlab-research-lookup, and for structured per-paper experimental-data extraction (sample sizes, effect sizes, quality scores) use alterlab-bgpt-search. Part of the AlterLab Academic Skills suite.

Produces KVKK-compliant (Law 6698, as amended by Law 7499 — published in the Official Gazette 12 Mar 2024, KVKK provisions effective 1 Jun 2024) data management plans for Turkish research, encoding the açık rıza (explicit consent) default basis, the Art. 28(1)(b) anonymization exemption as the primary compliance lever, the Art. 6 special-category regime for health/genetic/biometric data, Art. 7 deletion/destruction/anonymization at purpose-end, the Art. 13 thirty-day data-subject response window, Art. 9 cross-border adequacy-decision rules for cloud/overseas data, and Art. 16 VERBIS pre-processing registration, with a KVKK-vs-GDPR crosswalk. Use when the user needs a KVKK data management plan, to anonymize a research dataset under Turkish law, a VERBIS check, or to fix EU DMP boilerplate for Turkey; for pure GDPR/HIPAA use alterlab-research-ethics. Part of the AlterLab Academic Skills suite.

Retrieves Türkiye higher-education program and admission statistics from YÖK Atlas (yokatlas.yok.gov.tr) — quotas (kontenjan), placements (yerleşen), minimum admission scores (taban puan), success ranks (başarı sırası), and per-title academic-staff counts — via the keyless yokatlas-py (>=0.6.0, MIT) wrapper over the JSON API at /api/tercih-kilavuz/ (search, universiteler, universite-programlar), with SearchFilters for puan türü (SAY/SÖZ/EA/DİL/TYT), university type (DEVLET/VAKIF), province, and success-rank ranges. Use when the request mentions YÖK Atlas, program statistics, kontenjan/quota data, taban puan/minimum admission score, başarı sırası/success rank, placement counts, or program staff counts for institutional research, program benchmarking, or student advising. For an academic's CV/profile/affiliation prefer alterlab-yok-akademik; for theses prefer alterlab-yok-tez. Legacy PHP endpoints are dead post-April-2026; only the JSON API is used. Part of the AlterLab Academic Skills suite.

Converts academic papers into promotional and presentation formats — interactive websites (Paper2Web), presentation videos (Paper2Video), and conference posters (Paper2Poster) from LaTeX or PDF sources. Use when disseminating a paper, preparing for a conference, building an explorable academic homepage, generating a video abstract, or producing a print-ready poster from a paper. Part of the AlterLab Academic Skills suite.

Writes structured, checklist-based manuscript and grant peer reviews — assesses methodology, statistical validity, reporting-standards compliance (CONSORT/STROBE/PRISMA), and gives constructive feedback. Use when writing a formal reviewer report, responding to a journal/grant review invitation, or revising a manuscript against reviewer criteria. For evaluating claims/evidence quality prefer alterlab-scientific-thinking; for a multi-reviewer mock-panel verdict use alterlab-paper-reviewer; for quantitative rubric scoring use alterlab-scholar-eval. Part of the AlterLab Academic Skills suite.

Query 40+ bioinformatics web services through one consistent Python API with bioservices (UniProt, KEGG, ChEMBL, Reactome, Ensembl, NCBI and more). Use when a workflow must hit multiple databases together, map identifiers across services, or run cross-database analyses — for quick single-database lookups use gget, for sequence and file manipulation use biopython. Part of the AlterLab Academic Skills suite.

Analyze Neuropixels 1.0/2.0 extracellular electrophysiology with SpikeInterface — load SpikeGLX/Open Ephys recordings, preprocess and motion-correct, run Kilosort4 spike sorting, compute quality metrics, apply Allen/IBL curation, and do AI-assisted visual inspection. Use when working with neural recordings, spike sorting, or extracellular electrophysiology, or when the user mentions Neuropixels, SpikeGLX, Open Ephys, Kilosort, quality metrics, or unit curation. Part of the AlterLab Academic Skills suite.

Design protein sequences for a fixed backbone with ProteinMPNN (Dauparas 2022) — message-passing inverse folding that outputs sequences predicted to fold to a given structure, with fixed positions, tied/symmetric chains, amino-acid bias, and a soluble-model variant. Use when inverse-folding a backbone PDB into sequences, redesigning selected positions, imposing symmetry across chains, or generating the sequence step of a design→fold→score loop. For pocket/interface design WITH a bound ligand, metal, or nucleic acid prefer alterlab-ligandmpnn; to GENERATE a new backbone prefer alterlab-rfdiffusion; to refold and validate a design prefer alterlab-alphafold; for generative multimodal design prefer alterlab-esm. Part of the AlterLab Academic Skills suite.

Generate de-novo protein backbones with RFdiffusion (Watson 2023) — a diffusion model for unconditional monomer generation, motif scaffolding, binder design against a target, and symmetric oligomers. Use when generating a new protein backbone from scratch, scaffolding a functional motif into a fold, designing a binder backbone to a target surface, or building symmetric assemblies; RFdiffusion produces the STRUCTURE, then alterlab-proteinmpnn designs its sequence and alterlab-alphafold validates it. For sequence design of an existing backbone prefer alterlab-proteinmpnn (or alterlab-ligandmpnn with a ligand); to fold a known sequence prefer alterlab-alphafold; for generative multimodal design prefer alterlab-esm. Part of the AlterLab Academic Skills suite.

Prepares ISO 13485 certification documentation for medical device Quality Management Systems (QMS) — gap analysis of existing documentation, Quality Manuals, required procedures and work instructions, and Medical Device Files. Use for ISO 13485 QMS documentation, conducting a documentation gap analysis, drafting a Quality Manual or SOP/work instruction, assembling a Medical Device File, identifying missing documentation for medical device certification, or when medical device regulations, QMS certification, FDA QMSR, or EU MDR are mentioned. Part of the AlterLab Academic Skills suite.

Develops, tests, and deploys clinical machine learning models with the PyHealth healthcare AI toolkit. Use when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare datasets (MIMIC-III/IV, eICU, OMOP), or implementing deep learning models for healthcare (RETAIN, SafeDrug, Transformer, GNN). 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.

Integrates the Benchling R&D platform via its REST API and SDK — access the registry (DNA, proteins), inventory, ELN entries and workflows, build Benchling Apps, and query the Benchling Data Warehouse. Use when automating Benchling lab data management, syncing sample registry or inventory records, scripting ELN entries/workflows, or running SQL against the Benchling Data Warehouse. Part of the AlterLab Academic Skills suite.

Writes liquid-handling protocols for Opentrons OT-2 and Flex robots using the official Opentrons Protocol API v2, with full access to v2 features for production-grade, officially compatible protocols. Use when authoring or running protocols specifically for Opentrons hardware. For multi-vendor automation or broader equipment control use pylabrobot instead. Part of the AlterLab Academic Skills suite.

Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server, returning 25+ fields per paper (methods, results, sample sizes, quality scores, conclusions). Use when running a literature review or evidence synthesis, or when needing experimental details (sample sizes, effect sizes, methods, quality scores) that abstracts alone do not provide. Part of the AlterLab Academic Skills suite.

Free Elicit-columns analog — ingest N PDFs (or any MarkItDown-supported document) and build a per-paper evidence table with user-defined columns, one row per paper and one column per attribute/question you want pulled from every source. Use when extracting structured data across many papers into a comparison table or data-extraction sheet (sample size, methods, main finding, effect, population/intervention/outcome, limitations), screening a corpus into a spreadsheet, or pulling the same fields from a stack of PDFs into CSV/Markdown. Routes conversion through MarkItDown; offline heuristic backend by default, optional LLM backend for precise answers. Part of the AlterLab Academic Skills suite.

Harvests article metadata, abstracts, and full-text PDFs from DergiPark (TÜBİTAK ULAKBİM's national journal-hosting platform, ~2,537 journals) via its verified platform-wide OAI-PMH endpoint (https://dergipark.org.tr/api/public/oai/; verbs Identify/ListSets/ListRecords/GetRecord; prefixes oai_dc/oai_mods/oai_marc/oai_etdms; setSpec=journal-slug), parses Highwire citation_* and DC.* meta tags on /pub/{slug}/article/{id} pages, pulls PDFs from the citation_pdf_url path, and emits BibTeX/RIS locally. Use when the user wants to harvest a Turkish journal, fetch DergiPark articles, list a journal archive, get BibTeX/RIS for a DergiPark paper, or read a journal aim-and-scope (öz/kapsam). For TR Dizin indexing status use alterlab-trdizin; for YÖK theses use alterlab-yok-tez; for academic profiles use alterlab-yok-akademik. Part of the AlterLab Academic Skills suite.

Creates professional infographics with Nano Banana Pro AI and smart iterative refinement, using Gemini 3 Pro for automated quality review and an optional Perplexity Sonar research phase for accurate, sourced data — supports 10 infographic types, 8 industry styles, and colorblind-safe palettes. Use when the request is for an infographic, data-story graphic, statistical poster, comparison chart, timeline, process/how-to visual, or list/social graphic that pairs a designed layout with figures. Use alterlab-scientific-schematics instead for technical flowcharts, CONSORT/PRISMA, pathways, or architecture diagrams; alterlab-generate-image for non-infographic illustrations. Part of the AlterLab Academic Skills suite.

Creates research posters in HTML/CSS with responsive layouts and easy visual integration, exportable to PDF or PPTX. Use ONLY when the user explicitly requests a PowerPoint/PPTX/PPT poster, an HTML/web-based poster, or a poster they will edit in PowerPoint, or when LaTeX is unavailable. For a standard/conference research poster with no format named, use alterlab-latex-posters instead; for a slide deck/oral-talk presentation, use alterlab-scientific-slides. Part of the AlterLab Academic Skills suite.

Evaluates scholarly work with the ScholarEval framework, producing structured assessment across research-quality dimensions (problem formulation, methodology, analysis, and writing) with quantitative rubric scores and actionable feedback. Use when scoring or grading a paper, thesis, or research output against rubric-style criteria, or benchmarking publication readiness across revisions. For checklist-based narrative reviewer reports prefer alterlab-peer-review; for evidence/claim quality and argument soundness use alterlab-scientific-thinking. Part of the AlterLab Academic Skills suite.

Quantifies bulk RNA-seq transcript abundance with salmon (v1.11.4 selective alignment) and kallisto (v0.52.0, kb-python workflow), builds a decoy-aware gentrome index, runs quant with --validateMappings --gcBias -l A, then imports estimates via tximport/tximeta with a tx2gene map and hands differential expression to alterlab-pydeseq2. Warns that salmon's index format changed to SSHash (rebuild pre-v1.11.2 indices) and that 'salmon alevin' was REMOVED (single-cell now uses piscem + alevin-fry). Use when quantifying RNA-seq transcript abundance, running salmon or kallisto, building a decoy-aware index, or wiring tximport to DESeq2; for differential expression use alterlab-pydeseq2, for FASTQ-to-VCF variant calling use alterlab-nf-core-sarek. Part of the AlterLab Academic Skills suite.

Processes and analyzes physiological biosignals with the NeuroKit2 Python toolkit — ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements, or when computing heart rate variability (HRV), event-related potentials, complexity measures, autonomic nervous system assessment, or multi-modal physiological signal integration for psychophysiology research. Part of the AlterLab Academic Skills suite.

Composes existing AlterLab skills into multi-agent agentic workflows using current Claude Code subagent and Claude Agent SDK orchestration patterns: parallel subagent fan-out, sequential pipelines, judge panels, adversarial verification, and loop-until-clean review cycles. Maps each pattern onto real skills (alterlab-research-pipeline, alterlab-deep-research, alterlab-citation-verifier, alterlab-paper-reviewer, alterlab-peer-review) with copyable delegation prompts, agent-definition frontmatter, and SDK query() snippets. Use when the request mentions multi-agent, subagents, agent team, parallel agents, orchestration, pipeline of skills, judge panel, adversarial verification, devil's advocate, loop until clean, chaining skills, dispatching agents, or composing skills into a workflow. Part of the AlterLab Academic Skills suite.

Integrates the LabArchives electronic lab notebook (ELN) via its REST API — access notebooks, manage entries and attachments, back up notebooks, and bridge to Protocols.io, Jupyter, and REDCap. Use when automating LabArchives ELN workflows, programmatically reading/writing notebook entries or attachments, backing up a LabArchives notebook, or syncing it with Protocols.io, Jupyter, or REDCap. Part of the AlterLab Academic Skills suite.

Programs lab automation with PyLabRobot, a vendor-agnostic Python framework that unifies control across Hamilton, Tecan, Opentrons, plate readers, and pumps, with simulation support. Use when controlling multiple equipment types or needing unified cross-vendor programming for complex, multi-vendor liquid-handling workflows. For Opentrons-only protocols with the official API, alterlab-opentrons may be simpler. Part of the AlterLab Academic Skills suite.

Guidance for open science practices — preregistration (OSF Registries, AsPredicted, PROSPERO, ClinicalTrials.gov), open data and FAIR principles, repository choice (Zenodo, Dryad, Figshare), open access routes (Green/Gold/Diamond), Creative Commons licensing, reproducible computational workflows (Docker, Binder, Code Ocean), registered reports, open peer review, and TOP Guidelines. Use when preregistering a study, writing the FAIR data-sharing and repository section of a grant data management plan (NSF, NIH, ERC, UKRI), choosing a data repository, navigating open access, or building reproducible analyses. For human-subjects ethics, IRB applications, informed consent, or GDPR/HIPAA compliance, defer to alterlab-research-ethics. Part of the AlterLab Academic Skills suite.

Search the web, run deep research, and extract content from known URLs via the Parallel Web Systems Chat API (OpenAI-compatible) and Extract API, returning synthesized summaries with inline citations. Use when running general web searches, current-events/market/technical lookups, broad information gathering, comprehensive research reports, or verifying a specific URL's content (requires PARALLEL_API_KEY). For scholarly paper retrieval or dual-backend academic lookup that auto-routes to Perplexity prefer alterlab-research-lookup instead. Part of the AlterLab Academic Skills suite.

Runs Qualitative Comparative Analysis — crisp-set (csQCA), multi-value (mvQCA), and fuzzy-set (fsQCA) — for small-to-medium-N configurational research: calibrating raw data into set membership, building and refining a truth table, and Boolean minimization into conservative / parsimonious / intermediate solutions with consistency and coverage. Because there is no maintained Python QCA library, it shells out to R's QCA package (calibrate, truthTable, minimize) via Rscript and documents that dependency honestly rather than faking a Python API. Use when the request mentions QCA, fsQCA, csQCA, configurational or set-theoretic analysis, necessary/sufficient conditions, truth tables, or calibration of conditions. For net-effect estimation of a single treatment prefer alterlab-causal-inference; for interpretive analysis prefer alterlab-qualitative-methods. Part of the AlterLab Academic Skills suite.

Applies social-network-analysis method discipline to relational data — degree/betweenness/closeness/eigenvector centrality and PageRank, community detection (Louvain and greedy-modularity native in networkx, Leiden via igraph), and inferential network models (ERGM) — choosing the measure that matches the substantive question and the right dependence assumptions, then routing computation to the existing networkx (and igraph/R) tooling. Use when the request mentions social network analysis, centrality, key players/brokerage, community or cluster detection in a network, ERGM, or modeling ties between nodes. For general graph algorithms and plotting prefer alterlab-networkx; for graph neural networks prefer alterlab-torch-geometric. Part of the AlterLab Academic Skills suite.

Manages citations for academic research — searches Google Scholar and PubMed for papers, extracts accurate metadata, validates citations, and generates properly formatted BibTeX entries. Use when finding papers, verifying citation information, converting DOIs to BibTeX, checking reference accuracy in scientific writing, or building a bibliography. Part of the AlterLab Academic Skills suite.

Creates professional research posters in LaTeX using beamerposter, tikzposter, or baposter — handles layout design, color schemes, multi-column formats, figure integration, and poster-specific visual-communication best practices. Use when building a conference or academic poster in LaTeX. For PowerPoint/PPTX poster output prefer pptx-posters instead. Part of the AlterLab Academic Skills suite.

Runs FASTQ-to-VCF germline and somatic variant calling via the Nextflow nf-core/sarek pipeline pinned to -r 3.8.1 — builds the samplesheet.csv (patient, sex, status, sample, lane, fastq_1, fastq_2), runs bwa-mem/bwa-mem2/dragmap alignment plus GATK4 MarkDuplicates and BQSR against the GATK GRCh38 resource bundle (dbSNP, Mills/1000G indels), and selects callers — explicitly correcting that sarek defaults to Strelka when --tools is unset (pass haplotypecaller for GATK best practice or deepvariant for CNN accuracy), with a non-Nextflow manual GATK4 fallback. Use when the user wants a variant-calling pipeline, FASTQ to VCF, germline or somatic SNV/indel calling, nf-core/sarek, GATK best-practices alignment-to-VCF, or BQSR/HaplotypeCaller/Mutect2/DeepVariant; annotate hits with alterlab-clinvar/alterlab-gnomad/alterlab-cosmic, parse VCFs with alterlab-pysam, store at scale with alterlab-tiledbvcf. Part of the AlterLab Academic Skills suite.

Build phylogenetic trees end-to-end from raw sequences — MAFFT multiple sequence alignment, optional TrimAl trimming, IQ-TREE 2 maximum-likelihood inference with model selection and bootstraps, FastTree for large datasets, then visualize with ETE3 or FigTree. Use when reconstructing trees from sequences (FASTA) for evolutionary analysis, microbial genomics, viral phylodynamics, protein-family studies, or molecular-clock dating. For manipulating/comparing an EXISTING Newick tree (prune, root, Robinson-Foulds, duplication/speciation events) use alterlab-etetoolkit; for plain sequence parsing/translation use alterlab-biopython. Part of the AlterLab Academic Skills suite.

Survival analysis and time-to-event modeling in Python with scikit-survival. Use when working with censored survival data, fitting Cox models, Random Survival Forests, Gradient Boosting models, or Survival SVMs, evaluating predictions with concordance index or Brier score, handling competing risks, or implementing any time-to-event workflow. Part of the AlterLab Academic Skills suite.

Graph Neural Networks with PyTorch Geometric (PyG) — node and graph classification, link prediction, GCN, GAT, and GraphSAGE layers, heterogeneous graphs, and molecular property prediction. Use when building or training GNNs for geometric deep learning on graph-structured data. 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.

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.

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.

Manages scientific protocols through the protocols.io API v3 — search, create, update, and publish protocols (with DOI), manage steps and materials, handle protocol/step discussions and comments, organize team workspaces, and upload/manage workspace files. Use when discovering, developing, publishing, or citing protocols.io protocols, collaborating on protocol steps/materials, recording experiment runs, or integrating protocols.io into lab documentation. Not for general ELN entries/notebooks (use alterlab-benchling or alterlab-labarchive) or lab-instrument/liquid-handler control. Part of the AlterLab Academic Skills suite.

Mixed methods research design and integration strategies for combining qualitative and quantitative approaches. Use when planning convergent, explanatory sequential, exploratory sequential, embedded, transformative, or multiphase designs; when integrating diverse data sources through merging, connecting, or embedding; when constructing joint displays or meta-inferences; or when evaluating quality criteria specific to mixed methods research. Covers Creswell & Plano Clark frameworks, notation systems, and software tools for integration. For single-strand qualitative coding (thematic analysis, grounded theory, saturation, inter-coder reliability) use alterlab-qualitative-methods; for questionnaire/Likert/instrument-validation mechanics use alterlab-survey-design. Part of the AlterLab Academic Skills suite.

Comprehensive survey and instrument design assistant supporting questionnaire construction, Likert scale design, question types (open/closed/matrix), response bias mitigation, sampling strategies (probability/non-probability), pilot testing, instrument validation (Cronbach's alpha, factor analysis), online survey tools (Qualtrics, REDCap, Google Forms), interview protocol development, focus group facilitation, mixed-mode surveys, and cultural adaptation of instruments. Use when designing a survey or questionnaire, building Likert scales, planning a sampling strategy, pilot testing, validating an instrument (Cronbach's alpha, factor analysis), developing an interview protocol, improving response rates, or working in Qualtrics or REDCap. For analyzing interview/focus-group data use alterlab-qualitative-methods; for qual+quant integration alterlab-mixed-methods; for test selection/power analysis alterlab-statistical-analysis; for IRB/consent alterlab-research-ethics. Part of the AlterLab Academic Skills suite.

Generates or edits raster images via AI models (FLUX.2, Gemini 3.1 Flash Image / "Nano Banana 2") through an OpenRouter API key. Use when the request is to generate or edit a photo, illustration, artwork, concept art, poster hero image, or presentation/slide visual asset — anything that is not a technical diagram or a data chart. For flowcharts, circuits, pathways, neural-net architectures, and technical/methodology diagrams use alterlab-scientific-schematics; for plotting numeric data (scatter, bar, line) use alterlab-matplotlib instead. Part of the AlterLab Academic Skills suite.