{
  "skill": "alterlab-skill-finder",
  "evals": [
    {
      "id": "use-alterlab-vague",
      "prompt": "Use AlterLab skills to help me analyze my clinical trial dataset — I don't know which one to pick.",
      "expected_output": "Invokes alterlab-skill-finder (Route mode): classifies the task, maps it to the data-science / clinical-research domain, names the best-fitting skill(s) (e.g. alterlab-statistical-analysis or alterlab-clinicaltrials), and applies it — telling the user which skill it picked and why.",
      "assertions": [
        {
          "type": "should_trigger",
          "value": true
        },
        {
          "type": "behavior",
          "value": "Selects and names a concrete AlterLab skill for the task instead of asking the user to know skill names."
        }
      ]
    },
    {
      "id": "which-skill-for-task",
      "prompt": "Which AlterLab skill should I use to find and fact-check papers on CRISPR off-target effects?",
      "expected_output": "Invokes alterlab-skill-finder: routes to the research/discovery skills (e.g. alterlab-deep-research or alterlab-pubmed) and names them, using the domain map / skill index rather than making the user memorize names.",
      "assertions": [
        {
          "type": "should_trigger",
          "value": true
        },
        {
          "type": "output_contains",
          "value": "alterlab-"
        },
        {
          "type": "behavior",
          "value": "Names the right AlterLab skill(s) for literature discovery and fact-checking."
        }
      ]
    },
    {
      "id": "alterflow-keyword-orchestrate",
      "prompt": "alterflow — investigate the link between sleep and memory consolidation and turn it into a publishable paper.",
      "expected_output": "Invokes alterlab-skill-finder in Orchestrate mode: FIRST asks 2-4 clarifying/scoping questions (quantitative vs qualitative, dataset/corpus, target output, depth) before executing, then selects the skills and proposes a multi-agent workflow (e.g. alterlab-research-pipeline: deep-research -> paper-writer -> paper-reviewer). Does not start executing before clarifying.",
      "assertions": [
        {
          "type": "should_trigger",
          "value": true
        },
        {
          "type": "output_contains",
          "value": "alterlab-research-pipeline"
        },
        {
          "type": "behavior",
          "value": "On the alterflow keyword, asks clarifying questions before execution and plans a multi-agent workflow composing the right skills."
        }
      ]
    },
    {
      "id": "alterflow-packaged-workflow",
      "prompt": "alterflow — before I submit my dissertation I want every reference and every cited claim checked, then an independent mock review of the whole thing.",
      "expected_output": "Invokes alterlab-skill-finder in Orchestrate mode. Asks a few scoping questions first (file format and location, which chapters, the contact email for polite API pools, how deep the review should go), then selects the packaged workflows documented in alterlab-research-workflows — citation-audit followed by review-panel (in Claude Code: /alterlab-workflows:citation-audit and /alterlab-workflows:review-panel) — shows the plan with a rough agent count, and waits for the user's go-ahead before running anything.",
      "assertions": [
        {
          "type": "should_trigger",
          "value": true
        },
        {
          "type": "output_contains",
          "value": "alterlab-research-workflows"
        },
        {
          "type": "behavior",
          "value": "Clarifies scope before executing, then routes to the packaged citation-audit and review-panel workflows with a cost estimate and a confirmation step."
        }
      ]
    },
    {
      "id": "dont-know-names",
      "prompt": "I don't know the names of your tools — what does AlterLab have to clean and model this messy survey dataset?",
      "expected_output": "Invokes alterlab-skill-finder: maps the task to the data-science and social-science-workflow domains and names concrete skills (e.g. alterlab-missing-data, alterlab-survey-analysis, alterlab-statistical-analysis) so the user does not need to know names.",
      "assertions": [
        {
          "type": "should_trigger",
          "value": true
        },
        {
          "type": "behavior",
          "value": "Surfaces concrete AlterLab skills for data cleaning / modeling when the user cannot name them."
        }
      ]
    },
    {
      "id": "route-to-uninstalled-plugin",
      "prompt": "Use AlterLab skills to help me write a KVKK-compliant data management plan for my TÜBİTAK 1001 project. (Only the alterlab-essentials plugins are installed.)",
      "expected_output": "Invokes alterlab-skill-finder (Route mode): picks alterlab-kvkk-dmp from the skill index, notices that its plugin (alterlab-turkish-academia) is not installed, and says how to get it — `/plugin install alterlab-turkish-academia@alterlab-academic-skills` then `/reload-plugins` in Claude Code, or the skill's zip from the latest release in the Claude app — instead of retrying the skill or searching for other tools.",
      "assertions": [
        {
          "type": "should_trigger",
          "value": true
        },
        {
          "type": "behavior",
          "value": "Names alterlab-kvkk-dmp and the alterlab-turkish-academia plugin, and gives the install step for the user's surface."
        },
        {
          "type": "behavior",
          "value": "Does not claim to have applied a skill that is not installed."
        }
      ]
    },
    {
      "id": "near-miss-deep-research",
      "prompt": "Run alterlab-deep-research in full mode on the topic of graphene batteries.",
      "expected_output": "Should NOT trigger this skill; the user already named a specific skill (alterlab-deep-research), so it is invoked directly — no routing needed.",
      "assertions": [
        {
          "type": "should_not_trigger",
          "value": true
        },
        {
          "type": "output_contains",
          "value": "alterlab-deep-research"
        }
      ]
    },
    {
      "id": "near-miss-workflow-orchestration",
      "prompt": "I want to hand-design a custom multi-agent workflow with a judge panel and adversarial verification composing three specific skills I'll name.",
      "expected_output": "Should NOT trigger this skill; defers to alterlab-workflow-orchestration. The user is designing the workflow mechanics themselves, which is that skill's job, not front-door routing.",
      "assertions": [
        {
          "type": "should_not_trigger",
          "value": true
        },
        {
          "type": "output_contains",
          "value": "alterlab-workflow-orchestration"
        }
      ]
    }
  ]
}

# AlterLab Skill Index

> **Generated** — do not edit by hand. Regenerate with `python3 scripts/gen_skill_index.py`; kept in sync with `skills.json`.

Every AlterLab skill (242) across 18 domains, with a one-line summary. The `alterlab-skill-finder` router uses this to name the right skill for a task.

## Core Pipeline — `core` (10)

- **`alterlab-citation-verifier`** — Verifies that every bibliography entry actually exists by cross-checking Crossref, OpenAlex, Semantic Scholar, and arXiv (no API key required) plus doi.org DOI registration, fuzzy-matching title and authors (difflib ratio >= 0.70), flagging retractions recorded by Crossref (including Retraction Watch data) or OpenAlex, and emitting per-entry JSON verdicts in the AlterLab citation-hallucination taxonomy (TF/PAC/IH/PH/SH); a companion script scores whether a cited abstract supports a claim (SH). Accepts BibTeX, DOI/arXiv lists, or pasted references, and reports unverified instead of passing anything it could not check
- **`alterlab-deep-research`** — Runs a 13-agent deep research pipeline for rigorous academic work on any topic across 7 modes (full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis), covering research-question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk-of-bias assessment, meta-analysis, APA 7.0 report compilation, editorial and devil's-advocate review, ethics review, and post-research literature monitoring
- **`alterlab-link-health`** — Audits and repairs Markdown link health across a skills repo via a four-tier pipeline (config hardening, intra-repo file-ref fixes, external URL substitutions, residual exclusions) and enforces a Tier 3 substitution guardrail that prevents regressions of previously-passing links; designed for lychee-based GitHub Actions link checkers but generalizes to markdown-link-check and similar tools
- **`alterlab-paper-reviewer`** — Simulates a full multi-reviewer journal review PANEL — 5 personas (Editor-in-Chief + 3 peer reviewers + a Devil's Advocate) debate a manuscript and produce a consensus Editorial Decision (accept/minor/major/reject) plus a prioritized Revision Roadmap. Modes: full, re-review (verify revisions addressed prior comments), quick, methodology-focus, Socratic guided
- **`alterlab-paper-writer`** — Drafts and revises academic papers through a 12-agent pipeline with hardened LaTeX output (apa7 class, PDF compiled from LaTeX), supporting IMRaD, literature review, theoretical, case study, policy brief, and conference paper structures, APA 7.0 (default), Chicago, MLA, IEEE, and Vancouver citation formats, bilingual abstracts (English plus the author's language, e.g. Turkish or Traditional Chinese), and multi-format output (LaTeX, DOCX, PDF, Markdown)
- **`alterlab-research-pipeline`** — Orchestrates the full academic research pipeline (research, write, integrity check, review, revise, re-review, re-revise, final integrity check, finalize), coordinating alterlab-deep-research, alterlab-paper-writer, and alterlab-paper-reviewer into a seamless 10-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates
- **`alterlab-skill-finder`** — The AlterLab front door and multi-agent launcher — routes a task to the right AlterLab skill(s) when the user invokes the suite without naming one, and for a multi-stage goal (or on the keyword 'alterflow', aliases 'alterresearch' / 'ultralab') it clarifies the goal with a few questions before anything runs, selects the skills the task needs, and runs a multi-agent workflow composing them (a packaged alterlab-workflows workflow, alterlab-research-pipeline, alterlab-ssci-orchestrator, or a bespoke plan via alterlab-workflow-orchestration). Triggers on 'use AlterLab skills', 'which AlterLab skill for X', 'is there an AlterLab skill for…', a multi-stage research goal, 'alterflow …', or any generic AlterLab request where the user does not know skill names
- **`alterlab-teaching-design`** — Designs courses and teaching materials using backward design (Wiggins & McTighe), constructive alignment (Biggs), and Bloom's taxonomy alignment, generating rubrics, formative and summative assessments, syllabi, lesson plans, inclusive-pedagogy guidance, and online/hybrid course architecture
- **`alterlab-thesis-supervisor`** — Supervises theses and dissertations end to end — structure guidance from proposal through defense, chapter-by-chapter writing support (introduction, literature review, methodology, results, discussion), supervision strategies, committee management, defense and viva voce preparation, timeline planning, feedback integration, examiner-expectation guidance, and formatting (APA 7, Chicago, university styles)
- **`alterlab-workflow-orchestration`** — Composes existing AlterLab skills into multi-agent agentic workflows using current Claude Code orchestration primitives — subagents (including nested subagents), dynamic workflow scripts, agent teams, forks, and the Claude Agent SDK: parallel 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, workflow-script skeletons, and SDK query() snippets

## Databases — `databases` (39)

- **`alterlab-alphafold-db`** — Access the AlphaFold DB of 240M+ AI-PREDICTED protein structures (v6, plus precomputed homodimer/heterodimer complexes) — retrieve models by UniProt accession, download PDB/mmCIF files, and analyze prediction confidence metrics (pLDDT, PAE)
- **`alterlab-arxiv`** — Search and retrieve preprints from arXiv via the Atom API by keywords, authors, arXiv IDs, date ranges, or subject categories
- **`alterlab-bindingdb`** — Query BindingDB for measured protein-ligand binding affinities (Ki, Kd, IC50, EC50) via its keyless REST API or the full TSV download, searching by target (UniProt ID), compound (SMILES), or pathogen
- **`alterlab-biorxiv`** — Search the bioRxiv preprint server and retrieve paper metadata or download PDFs via its API
- **`alterlab-brenda`** — Access the BRENDA enzyme database via its SOAP API to retrieve kinetic parameters (Km, kcat, Ki), reaction equations, organism data, and substrate-specific enzyme information indexed by EC number
- **`alterlab-cbioportal`** — Query cBioPortal via its keyless REST API for cancer genomics across TCGA, GENIE, MSK-IMPACT and hundreds of studies — somatic mutations, copy-number alterations (GISTIC), mRNA/protein expression, structural variants, and patient-level clinical/survival data
- **`alterlab-chembl`** — Query ChEMBL via the chembl_webresource_client Python client for curated bioactive molecules and drug-like compound libraries at scale — search compounds by structure or physicochemical properties, retrieve bioactivity measurements (IC50, Ki, EC50), and find inhibitors of a target
- **`alterlab-clinicaltrials`** — Query ClinicalTrials.gov via its API v2 to search trials by condition, drug, location, recruitment status, or phase and retrieve trial details by NCT ID
- **`alterlab-clinpgx`** — Access ClinPGx pharmacogenomics data (the successor to PharmGKB) to query gene-drug interactions, CPIC/DPWG dosing guidelines, drug labels, and pharmacogene records
- **`alterlab-clinvar`** — Query NCBI ClinVar via the E-utilities API or FTP for the clinical significance (pathogenicity) of human germline genetic variants, searching by gene, variant, condition, or genomic position and interpreting ACMG/AMP classifications and review-status star ratings
- **`alterlab-cosmic`** — Access the COSMIC catalogue of somatic mutations in cancer to query somatic mutations, the Cancer Gene Census, mutational signatures, and gene fusions (authentication required)
- **`alterlab-datacommons`** — Query Google Data Commons for public statistical data aggregated from global sources, resolving geographic entities and pulling time-series statistics
- **`alterlab-depmap`** — Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), drug sensitivity data, and gene effect profiles
- **`alterlab-drugbank`** — Access and analyze drug information from the DrugBank database — drug properties, interactions, targets, pathways, chemical structures, and pharmacology data
- **`alterlab-ena`** — 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
- **`alterlab-ensembl`** — 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
- **`alterlab-fda`** — Query the openFDA API for drugs, medical devices, adverse event reports, recalls, regulatory submissions (510k, PMA), and substance identification (UNII)
- **`alterlab-gene-db`** — 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
- **`alterlab-geo`** — 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
- **`alterlab-gnomad`** — Query gnomAD (Genome Aggregation Database) for population allele frequencies and gene constraint scores (pLI, LOEUF) reflecting loss-of-function intolerance
- **`alterlab-gtex`** — 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)
- **`alterlab-gwas`** — Query the NHGRI-EBI GWAS Catalog REST API v2 for curated SNP-trait associations, retrieving variants by rs ID, disease/trait (EFO/MONDO), gene, or study (GCST) with p-values, effect sizes, and ancestry, and locate full harmonised summary statistics on the FTP site
- **`alterlab-hmdb`** — 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
- **`alterlab-imaging-data-commons`** — 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
- **`alterlab-interpro`** — 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)
- **`alterlab-jaspar`** — 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
- **`alterlab-kegg`** — 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
- **`alterlab-metabolomics-wb`** — Access the NIH Metabolomics Workbench via its REST API (4,500+ public studies), querying metabolites, RefMet standardized nomenclature, MS/NMR data, m/z mass searches, and study metadata
- **`alterlab-monarch`** — Query the Monarch Initiative knowledge graph for disease-gene-phenotype associations across species, integrating OMIM, ORPHANET, HPO, ClinVar, and model organism databases
- **`alterlab-openalex`** — Query and analyze scholarly literature using the OpenAlex API across 300M+ works, retrieving papers, authors, institutions, citations, and open access status
- **`alterlab-opentargets`** — Query the Open Targets Platform GraphQL API for target-disease associations, tractability and safety data, genetics/omics evidence, and known drugs
- **`alterlab-pdb`** — 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
- **`alterlab-pubchem`** — Query PubChem via the PUG-REST API and PubChemPy across 119M+ compounds, searching by name, CID, or SMILES and retrieving molecular properties, bioactivity, and similarity/substructure matches
- **`alterlab-pubmed`** — Provide direct REST API access to PubMed via the NCBI E-utilities API, supporting advanced Boolean/MeSH queries, batch processing, and citation management
- **`alterlab-reactome`** — Query the Reactome REST API for pathway analysis, over-representation/enrichment, gene-to-pathway mapping, disease pathways, molecular interactions, and expression analysis
- **`alterlab-string-db`** — Query the STRING API for protein-protein interactions (59M proteins, 20B+ interactions across 12,500+ organisms), building interaction networks, discovering functional partners, and running GO/KEGG/Pfam enrichment on protein lists
- **`alterlab-uniprot`** — 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
- **`alterlab-uspto`** — Access USPTO patent and trademark data through the Open Data Portal (ODP) APIs — Patent File Wrapper search, examination history (the PEDS successor), continuity, assignments, office actions, PTAB decisions — and trademark status via TSDR
- **`alterlab-zinc-db`** — Access the ZINC database of 230M+ commercially available (purchasable) compounds, searching by ZINC ID or SMILES, running similarity searches, and downloading 3D-ready structures

## Bioinformatics — `bioinformatics` (38)

- **`alterlab-alphafold`** — Predict protein 3D structures with AlphaFold2 via ColabFold — MMseqs2-accelerated MSAs, monomer and AlphaFold2-Multimer complex folding, and confidence-based validation (pLDDT, pTM/ipTM, PAE)
- **`alterlab-anndata`** — Build, slice, concatenate, read, and write AnnData annotated data matrices (obs, var, X, layers, obsm, uns) — the scverse data STRUCTURE, not an analysis pipeline
- **`alterlab-arboreto`** — Infer gene regulatory networks (GRNs) from expression matrices using arboreto's scalable GRNBoost2 and GENIE3 tree-ensemble algorithms with Dask-distributed computation
- **`alterlab-biopython`** — Manipulate biological sequences, parse FASTA/GenBank/PDB files, run phylogenetics, and access NCBI/PubMed programmatically via Biopython (Bio.SeqIO, Bio.Entrez, Bio.PDB, Bio.Blast)
- **`alterlab-bioservices`** — Query 40+ bioinformatics web services through one consistent Python API with bioservices (UniProt, KEGG, ChEMBL, Reactome, Ensembl, NCBI and more)
- **`alterlab-blast`** — Runs NCBI BLAST+ 2.17.0 sequence searches from the command line: makeblastdb (with -parse_seqids), blastn/blastp/blastx/tblastn with tabular -outfmt 6/7 for parsing, correct -task choice (megablast vs blastn vs blastn-short), -taxids/-negative_taxids taxonomic scoping, and -mt_mode multithreading; plus a DIAMOND blastp --ultra-sensitive path for large protein searches. Warns that -max_target_seqs is a heuristic keep-count, not a top-N best-hits filter
- **`alterlab-boltz`** — Co-fold biomolecular complexes with Boltz-2, an open AlphaFold3-style model — predict protein + ligand (SMILES/CCD), protein + nucleic-acid, and multi-chain structures in one pass, with binding-affinity prediction
- **`alterlab-borzoi`** — Predict genome-wide functional genomics tracks from DNA sequence with Borzoi (Linder 2025) — a sequence-to-function model outputting RNA-seq, CAGE, ATAC, and ChIP coverage across long context, used to score non-coding and regulatory variant effects
- **`alterlab-cellxgene`** — Query the CZ CELLxGENE Census (200M+ cells) programmatically via cellxgene-census and TileDB-SOMA, slicing expression by tissue, disease, or cell type and returning AnnData
- **`alterlab-chai`** — Predict biomolecular complexes with Chai-1, an open AlphaFold3-style model that folds multi-entity assemblies (proteins, ligands, nucleic acids) from a single typed FASTA — strong on antibody–antigen and protein–ligand complexes, with optional MSA and restraint inputs
- **`alterlab-cobrapy`** — Build and analyze genome-scale constraint-based metabolic models with COBRApy — flux balance analysis (FBA), flux variability analysis (FVA), gene and reaction knockouts, flux sampling, and SBML model I/O
- **`alterlab-deeptools`** — Process and visualize deep-sequencing coverage with the deepTools CLI — convert BAM to bigWig (bamCoverage), build log2 ratio tracks (bamCompare), run QC (multiBamSummary correlation, PCA, plotFingerprint), apply the ATAC-seq Tn5 shift (alignmentSieve --ATACshift), and make TSS/peak heatmaps and profiles (computeMatrix, plotHeatmap, plotProfile)
- **`alterlab-esm`** — Run ESM protein language models — ESMC for embeddings and representations, ESMFold2 for structure prediction, and ESM3 for generative multimodal protein design across sequence, structure, and function — locally or through the hosted Biohub Platform API (formerly Forge)
- **`alterlab-etetoolkit`** — 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
- **`alterlab-flowio`** — Parse and write FCS (Flow Cytometry Standard) files v2.0-3.1 with FlowIO — extract event data as NumPy arrays, read $-keyword metadata and channel/parameter definitions, and convert events to CSV or pandas DataFrame
- **`alterlab-gget`** — Run fast one-liner queries to 20+ bioinformatics databases from the gget CLI or Python — gene info (Ensembl), BLAST, AlphaFold structures, Enrichr enrichment, and more
- **`alterlab-glycoengineering`** — Analyze and engineer protein glycosylation — scan sequences for N-glycosylation sequons (N-X-S/T), predict O-glycosylation hotspots, and reach curated glycoengineering tools (NetOGlyc, GlycoShield, GlycoWorkbench)
- **`alterlab-histolab`** — Extract and preprocess tiles from whole-slide images (WSI) with histolab — OpenSlide-backed slide loading, tissue detection and masks, Random/Grid/Score tile extraction, and image/morphological filters for H&E preprocessing
- **`alterlab-lamindb`** — Manage, annotate, and trace biological data with LaminDB, an open-source FAIR data framework that makes datasets queryable, versioned, and reproducible
- **`alterlab-ligandmpnn`** — 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
- **`alterlab-neuropixels`** — 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
- **`alterlab-nf-core-sarek`** — Runs FASTQ-to-VCF germline and somatic variant calling via the Nextflow nf-core/sarek pipeline pinned to -r 3.10.0 — 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
- **`alterlab-pathml`** — Run full computational-pathology workflows with PathML — whole-slide-image (WSI) analysis across 160+ slide formats, multiplexed immunofluorescence (CODEX, Vectra, MERFISH), nucleus segmentation/classification (HoVer-Net, HACTNet), tissue- and cell-graph construction, HDF5 dataset management, and deep-learning model training on pathology data
- **`alterlab-phylogenetics`** — Build phylogenetic trees end-to-end from raw sequences — MAFFT multiple sequence alignment, optional TrimAl trimming, IQ-TREE 3 maximum-likelihood inference with model selection and bootstraps, FastTree for large datasets, then visualize with ETE3 or FigTree
- **`alterlab-proteinmpnn`** — 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
- **`alterlab-pydeseq2`** — Run differential gene expression analysis on bulk RNA-seq count matrices with PyDESeq2, the Python port of DESeq2 — size-factor normalization, dispersion estimation, Wald tests, FDR (Benjamini-Hochberg) correction, and volcano/MA plots
- **`alterlab-pyopenms`** — Build complete mass-spectrometry workflows with pyOpenMS — feature detection, peptide identification, protein quantification, and full LC-MS/MS pipelines across many MS file formats (mzML, mzXML) and algorithms
- **`alterlab-pysam`** — Read and write genomic alignment and variant files in Python with pysam (htslib bindings) — SAM/BAM/CRAM alignments, VCF/BCF variants, and FASTA/FASTQ sequences, plus region extraction and per-base coverage/pileup
- **`alterlab-qiime2-amplicon`** — Runs 16S/ITS amplicon (microbiome) analysis with the QIIME 2 distribution (2026.7; the "amplicon" distribution was renamed "qiime2" in 2026.4) in the correct order: manifest import, cutadapt trim-paired primer removal BEFORE dada2 denoise-paired (trunc-len chosen from the demux quality .qzv), feature-classifier classify-sklearn against a version-matched SILVA 138 or Greengenes2 classifier, and diversity core-metrics-phylogenetic — teaching the .qza/.qzv artifact-and-provenance model and the 2026.1 feature-table summarize change (the former summarize_plus)
- **`alterlab-rfdiffusion`** — 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
- **`alterlab-rnaseq-quant`** — Quantifies bulk RNA-seq transcript abundance with salmon 2.x (the Rust rewrite; selective alignment or --sketch) and kallisto (v0.52.0, kb-python workflow), builds a decoy-aware gentrome index, runs quant with --gcBias -l A, then imports estimates via tximport/tximeta with a tx2gene map and hands differential expression to alterlab-pydeseq2. Warns that salmon 2.0 cannot read C++/pufferfish indices (rebuild every index), that --validateMappings is now accepted-but-ignored, and that 'salmon alevin' was REMOVED (single-cell now uses piscem + alevin-fry)
- **`alterlab-scanpy`** — Run the standard single-cell RNA-seq analysis pipeline with Scanpy on AnnData — QC filtering, normalization, dimensionality reduction (PCA, UMAP, t-SNE), Leiden/Louvain clustering, marker/differential expression, PAGA trajectories, and plotting
- **`alterlab-scgpt`** — Apply the scGPT single-cell foundation model (Cui 2024) to annotate and embed cells — zero-shot and fine-tuned cell-type annotation, gene/cell embeddings, batch integration, and gene-regulatory / perturbation inference from AnnData
- **`alterlab-scikit-bio`** — 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
- **`alterlab-scvelo`** — Run RNA velocity analysis with scVelo on single-cell RNA-seq data — estimate cell-state transitions from spliced/unspliced mRNA dynamics, infer trajectory direction, compute latent time, and identify driver genes
- **`alterlab-scvi-tools`** — 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)
- **`alterlab-squidpy-spatial`** — Analyzes spatial transcriptomics with squidpy (1.8.x) on AnnData and SpatialData objects, routing platforms correctly: Visium spots use spatial_neighbors(coord_type='grid') and pair with deconvolution, while Xenium/MERFISH single-cell data use coord_type='generic'/Delaunay neighbors and spatialdata-io readers (xenium, visium_hd, merscope). Runs sq.gr.spatial_neighbors, nhood_enrichment, co_occurrence, spatial_autocorr (Moran's I for spatially variable genes), ripley, and ligrec
- **`alterlab-tiledbvcf`** — Store and query genomic variant data at scale with TileDB-VCF — ingest VCF/BCF into compressed TileDB arrays, add samples incrementally, run fast parallel region/sample queries, and export back to VCF

## Cheminformatics — `cheminformatics` (12)

- **`alterlab-datamol`** — Wraps RDKit in a high-level, pandas-friendly datamol interface with sensible defaults for everyday drug discovery — SMILES/SDF loading into DataFrames, molecule standardization, descriptors, fingerprints, Butina clustering, 3D conformer generation, scaffold analysis, and parallel batch processing, returning native rdkit.Chem.Mol objects
- **`alterlab-deepchem`** — Runs molecular machine learning with DeepChem — diverse featurizers, pre-built MoleculeNet benchmark datasets, and pre-trained models (ChemBERTa, GROVER) for property prediction (ADMET, toxicity, solubility) via traditional ML or graph neural networks
- **`alterlab-diffdock`** — Predicts protein-ligand binding poses with DiffDock diffusion-based molecular docking from PDB structures and SMILES, producing pose confidence scores for virtual screening and structure-based drug design
- **`alterlab-matchms`** — Computes mass-spectral similarity and identifies compounds for metabolomics with matchms — comparing mass spectra, scoring similarity (cosine, modified cosine), and searching spectral libraries to annotate unknowns
- **`alterlab-medchem`** — Applies medicinal-chemistry filters with the medchem library — drug-likeness rules (Lipinski, Veber), PAINS filters, structural alerts, and molecular complexity metrics for compound prioritization and library cleanup
- **`alterlab-molecular-dynamics`** — Runs and analyzes molecular dynamics simulations with OpenMM and MDAnalysis — setting up protein and small-molecule systems, assigning force fields, running energy minimization and production MD, and analyzing trajectories (RMSD, RMSF, contact maps, free energy surfaces)
- **`alterlab-molfeat`** — Featurizes molecules for machine learning with molfeat — ECFP/MACCS/MAP4 fingerprints, RDKit and Mordred physicochemical descriptors, pharmacophore and shape descriptors, and pretrained embeddings (ChemBERTa, ChemGPT, CheMeleon) exposed as scikit-learn transformers that convert SMILES into feature vectors
- **`alterlab-primekg`** — Queries the Precision Medicine Knowledge Graph (PrimeKG) for multiscale biomedical relationships across genes, drugs, diseases, phenotypes, pathways, and biological processes
- **`alterlab-pytdc`** — Loads Therapeutics Data Commons (TDC, PyTDC) AI-ready drug-discovery datasets and benchmarks — ADME, toxicity, drug-target interaction (DTI), scaffold splits, and molecular oracles for therapeutic ML and pharmacological prediction
- **`alterlab-rdkit`** — Provides the RDKit cheminformatics toolkit for low-level, fine-grained molecular primitives — SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure/SMARTS search, 2D/3D coordinate generation, similarity, and reaction handling
- **`alterlab-rowan`** — Drives the Rowan cloud quantum-chemistry platform via its Python API for computational chemistry — pKa prediction, geometry optimization, conformer searching, molecular property calculations, protein-ligand docking (AutoDock Vina), and AI protein cofolding (Chai-1, Boltz-1/2), with cloud compute and no local setup
- **`alterlab-torchdrug`** — 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

## Clinical Research — `clinical-research` (7)

- **`alterlab-clinical-decision`** — Generates professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings — biomarker-stratified patient cohort analyses with outcomes and evidence-based treatment recommendation reports with decision algorithms, supporting GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance, output as publication-ready LaTeX/PDF
- **`alterlab-clinical-reports`** — Writes comprehensive clinical reports — case reports (CARE guidelines), diagnostic reports (radiology, pathology, lab), clinical trial reports (ICH-E3, SAE, CSR), and patient documentation (SOAP notes, H&P, discharge summaries) — with templates, regulatory compliance (HIPAA, FDA, ICH-GCP), and validation tools
- **`alterlab-iso13485`** — 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
- **`alterlab-neurokit2`** — Processes and analyzes physiological biosignals with the NeuroKit2 Python toolkit — ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals
- **`alterlab-pydicom`** — Reads, writes, and manipulates DICOM (Digital Imaging and Communications in Medicine) medical imaging files with the pydicom Python library
- **`alterlab-pyhealth`** — Develops, tests, and validates clinical machine learning models with the PyHealth 2.x healthcare AI toolkit
- **`alterlab-treatment-plans`** — Generates concise (3-4 page), focused medical treatment plans in LaTeX/PDF format across all clinical specialties — general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management — using SMART goal frameworks, evidence-based interventions with minimal citations, HIPAA compliance, and professional formatting

## Data Science — `data-science` (22)

- **`alterlab-dask`** — Scales pandas/NumPy workflows beyond memory with Dask distributed computing — parallel DataFrames, arrays, delayed task graphs, and cluster execution
- **`alterlab-eda`** — Exploratory data analysis (EDA) on a scientific data file — auto-detects the format, runs structure/quality/statistics checks, and writes a markdown EDA report with downstream recommendations
- **`alterlab-networkx`** — Creates, analyzes, and visualizes complex networks and graphs in Python with NetworkX
- **`alterlab-polars`** — Fast in-memory DataFrame analytics with Polars — lazy evaluation, parallel execution, and an Apache Arrow backend for datasets that fit in RAM
- **`alterlab-pufferlib`** — Scales reinforcement learning with PufferLib — high-throughput parallel training (PuffeRL), vectorized environments, and native multi-agent systems achieving 2-10x speedups over standard implementations
- **`alterlab-pymc`** — Bayesian modeling and probabilistic programming with PyMC 6 and ArviZ 1.x — hierarchical models, MCMC (NUTS via PyMC, nutpie, NumPyro, or BlackJAX), variational inference, PSIS-LOO model comparison, and prior/posterior predictive checks
- **`alterlab-pymoo`** — Multi-objective optimization with pymoo — NSGA-II, NSGA-III, MOEA/D, Pareto-front computation, constraint handling, and standard benchmarks (ZDT, DTLZ)
- **`alterlab-pytorch-lightning`** — Scalable deep-learning training with PyTorch Lightning — organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, build data pipelines and callbacks, log to W&B or TensorBoard, and run distributed training (DDP, FSDP, DeepSpeed)
- **`alterlab-scikit-learn`** — Classical machine learning in Python with scikit-learn — algorithms, preprocessing, pipelines, and best-practice reference documentation
- **`alterlab-scikit-survival`** — Survival analysis and time-to-event modeling in Python with scikit-survival
- **`alterlab-shap`** — Model interpretability and explainability with SHAP (SHapley Additive exPlanations) — feature importance and plots (waterfall, beeswarm, bar, scatter, force, heatmap)
- **`alterlab-simpy`** — Process-based discrete-event simulation in Python with SimPy — processes, queues, shared resources, and time-based events
- **`alterlab-stable-baselines3`** — Trains single-agent reinforcement learning agents with Stable-Baselines3 — PPO, SAC, DQN, TD3, DDPG, and A2C behind a scikit-learn-like API
- **`alterlab-statistical-analysis`** — Guided statistical analysis with hypothesis-test selection, assumption checking, effect sizes, power analysis, and APA-formatted reporting using scipy.stats, statsmodels, and pingouin (Bayesian alternatives with PyMC)
- **`alterlab-statsmodels`** — Statistical modeling in Python with statsmodels — OLS/WLS/GLS, GLM, discrete-choice and count models, mixed models, ARIMA/SARIMAX/VAR, with diagnostics, robust standard errors, and coefficient-level inference
- **`alterlab-sympy`** — Symbolic mathematics in Python with SymPy — solve equations algebraically, perform calculus (derivatives, integrals, limits), manipulate algebraic expressions, work with symbolic matrices, and generate executable code from formulas
- **`alterlab-timesfm`** — Forecasts time series zero-shot with Google's TimesFM foundation models — TimesFM 2.5 (200M, Apache-2.0 weights; ForecastConfig API, XReg covariates) and TimesFM 3.0 (~330M, multivariate with native past/future covariates; non-commercial weights) — producing point forecasts and quantile prediction intervals from CSV/DataFrame/array inputs, with a preflight system checker for RAM/GPU
- **`alterlab-torch-geometric`** — Graph Neural Networks with PyTorch Geometric (PyG) — node and graph classification, link prediction, GCN, GAT, and GraphSAGE layers, heterogeneous graphs, and molecular property prediction
- **`alterlab-transformers`** — Loads, runs, and fine-tunes pretrained models with Hugging Face Transformers v5 (PyTorch-only) — pipeline() inference for chat-model text generation, text classification, NER, zero-shot, speech recognition, image classification, object detection, and image-text-to-text VLMs; AutoModel/AutoTokenizer loading with dtype, device_map and bitsandbytes quantization; generate() decoding control; and Trainer fine-tuning with optional PEFT/LoRA
- **`alterlab-umap`** — Nonlinear dimensionality reduction with UMAP — fast manifold learning for 2D/3D visualization, clustering preprocessing (e.g., HDBSCAN), and supervised or parametric UMAP
- **`alterlab-vaex`** — Out-of-core tabular analytics with Vaex — memory-mapped HDF5/Arrow/Parquet via vaex.open, lazy virtual columns, delayed single-pass aggregations on billion-row tables, binned histograms/heatmaps, and vaex.ml transformers on one machine. Vaex is in minimal-maintenance mode (vaex-core 4.19 from Sep 2025 supports only Python 3.9–3.12 and pandas < 3), so use it to run, fix, or migrate existing Vaex code; for new larger-than-RAM work prefer Polars lazy/streaming queries (alterlab-polars) or Dask (alterlab-dask)
- **`alterlab-zarr`** — Chunked, compressed N-dimensional arrays for cloud storage with Zarr — parallel I/O, S3/GCS integration, and NumPy/Dask/Xarray compatibility

## Visualization — `visualization` (9)

- **`alterlab-figure-qa`** — Verify publication figures with a render-then-check QA pass — data-fidelity against every underlying row, axis/label floor-and-ceiling legibility, bounding-box collision detection for overlapping text/markers, and 300-dpi print-readiness
- **`alterlab-generate-image`** — Generates or edits raster images via AI models (FLUX.2, Gemini 3.1 Flash Image / "Nano Banana 2") through an OpenRouter API key
- **`alterlab-infographics`** — Creates professional infographics with Nano Banana Pro AI and smart iterative refinement, using Gemini 3.1 Pro for automated quality review and an optional Perplexity Sonar research phase for sourced data — supports 10 infographic types, 8 industry styles, and colorblind-safe palettes
- **`alterlab-matplotlib`** — 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
- **`alterlab-mermaid`** — Writes Markdown documents and text-based Mermaid diagrams (flowcharts, sequence, class, ER, gantt, state, and more) with full style guides, 24 diagram-type references, and 9 document templates
- **`alterlab-plotly`** — Builds INTERACTIVE charts with the Plotly Python library (plotly.express / graph_objects) — hover tooltips, zoom/pan, animations, rangesliders, 3D rotation, and standalone HTML/web-embeddable output
- **`alterlab-scientific-schematics`** — Creates publication-quality scientific diagrams with Nano Banana 2 AI and smart iterative refinement, using Gemini 3.1 Pro Preview for quality review and regenerating only when quality falls below the document-type threshold
- **`alterlab-scientific-viz`** — Orchestrates matplotlib, seaborn, and plotly with opinionated publication styles to produce journal-ready figures
- **`alterlab-seaborn`** — Builds statistical plots with the seaborn Python library and pandas DataFrame integration, on attractive matplotlib-based defaults

## Writing Tools — `writing-tools` (14)

- **`alterlab-academic-career`** — Prepares academic career documents and professional-development materials for faculty and researchers
- **`alterlab-ai-use-disclosure`** — Helps faculty and researchers disclose generative-AI use and comply with the rules for manuscripts, grant proposals, peer review, theses and figures. Walks a venue → policy → placement decision tree over policies verified on 2026-09-23 (ICMJE, Springer Nature/Nature, Elsevier, Wiley, Taylor & Francis, Sage, IEEE, PLOS, arXiv; NIH NOT-OD-25-132 and NOT-OD-23-149, NSF, UKRI, ERC, TÜBİTAK; YÖK's 2024 ethics guide; EU AI Act Article 50), drafts English and Turkish statements, and ships scripts/disclosure_builder.py to emit a statement plus warnings where a policy forbids the use
- **`alterlab-citation-mgmt`** — Manages citations for academic research — searches Google Scholar and PubMed for papers, extracts complete metadata from DOIs, PMIDs, and arXiv IDs (CrossRef, doi.org content negotiation, NCBI E-utilities, arXiv API), validates BibTeX entries for required fields, format, and duplicates, and generates or cleans properly formatted BibTeX
- **`alterlab-hypothesis-gen`** — Formulates structured, testable hypotheses from experimental observations using a scientific-method framework — derives predictions, proposes mechanisms, and designs experiments to test them, then renders a LaTeX report
- **`alterlab-latex-posters`** — 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
- **`alterlab-literature-review`** — Conducts comprehensive, systematic literature reviews across multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar), with PRISMA 2020 flow tracking, study screening (title/abstract and full-text), evidence-table extraction, and risk-of-bias assessment (RoB 2, ROBINS-I, AMSTAR 2), producing professionally formatted markdown documents and PDFs with verified citations in multiple styles (APA, Nature, Vancouver)
- **`alterlab-paper-2-web`** — Converts academic papers into promotional and presentation formats with the third-party Paper2All pipeline (LLM calls routed through OpenRouter/OpenAI) — interactive websites (Paper2Web), presentation videos (Paper2Video), and conference posters (Paper2Poster) from a paper PDF and its LaTeX sources
- **`alterlab-peer-review`** — Writes structured, checklist-based single-reviewer reports for manuscripts and grant proposals — assesses methodology, statistical validity, reporting-standards compliance (CONSORT 2025, SPIRIT 2025, STROBE, PRISMA 2020, ARRIVE 2.0), reproducibility, and ethics, and gives constructive, prioritized feedback while respecting reviewer confidentiality and AI-use rules
- **`alterlab-pptx-posters`** — 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
- **`alterlab-research-grants`** — Writes competitive research grant proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC — applies agency-specific formatting and current review criteria (NIH Simplified Review Framework, NSF Intellectual Merit and Broader Impacts under PAPPG 24-1), prepares budgets and justifications, drafts Specific Aims, broader-impacts, significance, and innovation narratives, and checks compliance, including funder rules on AI-assisted applications
- **`alterlab-scholar-eval`** — Evaluates scholarly work with a ScholarEval-inspired eight-dimension rubric, producing structured assessment across research-quality dimensions (problem formulation, literature, methodology, data, analysis, results, writing, and citations) with quantitative 1-5 rubric scores, weighted aggregates, and actionable feedback
- **`alterlab-scientific-slides`** — Builds slide decks for research talks as AI-generated slide images (Nano Banana Pro via OpenRouter), PowerPoint, or LaTeX Beamer, providing slide structure, design templates, timing guidance, and visual validation
- **`alterlab-scientific-writing`** — Writes scientific manuscripts in full flowing paragraphs (never bullet points) via a two-stage process — section outlines with key points using alterlab-research-lookup, then conversion to prose — applying IMRAD structure, citations (APA/AMA/Vancouver), figures/tables, and current reporting guidelines (CONSORT 2025, STROBE, PRISMA 2020, TRIPOD+AI)
- **`alterlab-venue-templates`** — Provides LaTeX templates, formatting requirements, and submission guidelines for major scientific venues (Nature, Science, PLOS, IEEE, ACM, Cell Press), conferences (NeurIPS, ICML, ICLR, CVPR, CHI), research posters, and grant proposals (NSF, NIH, DOE, DARPA). Also covers venue-specific writing style (tone, abstract format, what reviewers prioritize)

## Lab Integrations — `lab-integrations` (9)

- **`alterlab-benchling`** — 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
- **`alterlab-dnanexus`** — 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
- **`alterlab-ginkgo-cloud`** — Submits and manages protocols on Ginkgo Bioworks Cloud Lab (cloud.ginkgo.bio), a web-based interface for autonomous lab execution on Reconfigurable Automation Carts (RACs), covering protocol selection, input preparation, pricing, and ordering workflows
- **`alterlab-labarchive`** — 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
- **`alterlab-latchbio`** — 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
- **`alterlab-omero`** — Manages microscopy image data on an OMERO server via the OMERO Python API (BlitzGateway) — access images, retrieve datasets, read pixel data, manage ROIs and annotations, and batch-process
- **`alterlab-opentrons`** — 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
- **`alterlab-protocolsio`** — Works with protocols.io through its REST API (v3 and v4 endpoints) and official MCP server — search and retrieve protocols by keyword, URI, or DOI; create private protocols, edit their metadata and steps, and publish them with a DOI; manage protocol and step discussions, workspaces, file-manager items, file uploads, experiment records, and organization exports
- **`alterlab-pylabrobot`** — Programs lab automation with PyLabRobot, a vendor-agnostic async Python framework that drives Hamilton STAR/Vantage, Tecan EVO, and Opentrons OT-2 liquid handlers plus plate readers, heater shakers, incubators, centrifuges, pumps, scales, and thermocyclers, with a chatterbox simulator and browser visualizer

## Domain-Specific — `domain-specific` (18)

- **`alterlab-adaptyv`** — 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)
- **`alterlab-aeon`** — Runs time series machine learning with the aeon library — classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search via scikit-learn compatible APIs
- **`alterlab-astropy`** — 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)
- **`alterlab-cirq`** — 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
- **`alterlab-digital-humanities`** — 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)
- **`alterlab-fluidsim`** — Runs computational fluid dynamics simulations with the FluidSim Python framework using pseudospectral FFT methods, with HPC support and output analysis
- **`alterlab-geniml`** — 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
- **`alterlab-geomaster`** — 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
- **`alterlab-geopandas`** — 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
- **`alterlab-gtars`** — Runs high-performance genomic interval analysis with gtars (databio), a Rust toolkit with Python bindings — the performance-critical backend for the geniml ML library
- **`alterlab-hypogenic`** — Runs automated LLM-driven hypothesis generation and testing on tabular datasets with HypoGeniC, combining literature insights with data-driven testing
- **`alterlab-modal`** — Runs Python code in the cloud with Modal — serverless containers, on-demand GPUs, and autoscaling
- **`alterlab-pennylane`** — Trains and differentiates quantum circuits with PennyLane, a hardware-agnostic quantum machine-learning framework with automatic differentiation and PyTorch/JAX integration
- **`alterlab-pymatgen`** — 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
- **`alterlab-qiskit`** — 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
- **`alterlab-qutip`** — Simulates open quantum systems with QuTiP, the Quantum Toolbox in Python, solving Lindblad master equations (mesolve), Monte Carlo trajectories (mcsolve), and unitary dynamics (sesolve)
- **`alterlab-remote-compute`** — 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)
- **`alterlab-social-science-methods`** — 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

## Document Tools — `document-tools` (3)

- **`alterlab-markitdown`** — Converts files and Office documents to clean, LLM-friendly Markdown with Microsoft MarkItDown (markitdown CLI, Python API, and markitdown-mcp server), supporting PDF, DOCX, PPTX, XLSX/XLS, images (EXIF metadata, LLM descriptions), audio (transcription), HTML, CSV, JSON, XML, ZIP archives, EPUB e-books, Outlook MSG, Jupyter notebooks, and YouTube transcript URLs, with OCR through the markitdown-ocr plugin or Azure Document Intelligence
- **`alterlab-open-notebook`** — Runs and scripts Open Notebook, a self-hosted open-source alternative to Google NotebookLM with a full REST API, for AI-powered research and document analysis
- **`alterlab-pdf-explore`** — 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

## Research Tools — `research-tools` (14)

- **`alterlab-bgpt-search`** — Search scientific papers and retrieve structured experimental evidence extracted from full-text studies via the BGPT MCP server (`search_papers`, plus `lookup_paper` by DOI), returning 25+ fields per paper (methods, results, sample sizes, quality scores, limitations, conclusions)
- **`alterlab-citation-graph`** — Free ResearchRabbit / Connected Papers analog — builds a citation and co-citation graph around one or more seed papers using the OpenAlex API. Walks both directions of the citation network (works the seed cites and works that cite the seed), ranks the discovered neighbourhood by co-citation strength and bibliographic coupling to surface the papers most central to a topic's literature, and exports the network as GraphML (Gephi / Cytoscape / yEd) and JSON
- **`alterlab-mixed-methods`** — Mixed methods research design and integration strategies for combining qualitative and quantitative approaches
- **`alterlab-open-science`** — 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
- **`alterlab-parallel-web`** — Search the web, run deep research, and extract content from known URLs via Parallel Web Systems — the Chat API (Beta, OpenAI-compatible `base`/`core` research models) for synthesized answers with inline citations and the Extract API v1 for URL content — with notes on the raw Search, Task, and Responses APIs
- **`alterlab-pdf-extract`** — 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
- **`alterlab-perplexity`** — Run AI web searches with real-time, citation-grounded answers using Perplexity Sonar models (sonar, sonar-pro, sonar-pro-search agentic search, sonar-reasoning-pro) via LiteLLM and a single OpenRouter API key
- **`alterlab-pyzotero`** — Interact with Zotero reference management libraries using the pyzotero Python client — retrieve, create, update, and delete items, collections, tags, and attachments via the Zotero Web API v3
- **`alterlab-qualitative-methods`** — Comprehensive qualitative research methods assistant supporting thematic analysis (Braun & Clarke), grounded theory (Strauss & Corbin; Charmaz), interpretative phenomenological analysis (IPA), content analysis, narrative inquiry, ethnography, case study methodology (Yin), coding techniques (open/axial/selective), NVivo-style workflows with Python alternatives, trustworthiness criteria (Lincoln & Guba), reflexivity, and member checking
- **`alterlab-research-ethics`** — International research ethics and compliance assistant supporting IRB/ethics board applications, informed consent drafting, data management plans, Belmont Report principles, Declaration of Helsinki (2024), GDPR compliance for research, HIPAA considerations, vulnerable populations protocols, deception research, confidentiality and anonymity, research integrity (fabrication/falsification/plagiarism), conflict of interest disclosure, and dual-use research oversight
- **`alterlab-research-lookup`** — Look up current research and scholarly papers by auto-routing each query to the best backend — the Parallel Web Systems Chat API (general research) or Perplexity sonar-pro-search via OpenRouter (academic paper searches) — and save every result with citations to sources/
- **`alterlab-scientific-brainstorm`** — Creative research ideation and exploration for open-ended brainstorming, surfacing interdisciplinary connections, challenging assumptions, and identifying research gaps
- **`alterlab-scientific-thinking`** — Evaluate scientific claims and evidence quality using evidence grading frameworks (GRADE, Cochrane risk-of-bias tools such as RoB 2 and ROBINS-I), assessing experimental design validity and identifying biases, confounders, statistical pitfalls, and logical fallacies
- **`alterlab-survey-design`** — 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

## Finance & Economics — `finance-economics` (7)

- **`alterlab-alpha-vantage`** — Accesses stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, company fundamentals, news sentiment, and 50+ technical indicators via the Alpha Vantage REST API (free API key from alphavantage.co; realtime/intraday data and full daily history need a premium key)
- **`alterlab-denario`** — 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
- **`alterlab-edgartools`** — Accesses, analyzes, and extracts data from SEC EDGAR filings using the edgartools Python library
- **`alterlab-fred`** — 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
- **`alterlab-hedgefund-monitor`** — 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)
- **`alterlab-market-research`** — 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)
- **`alterlab-usfiscaldata`** — Queries the U.S. Treasury Fiscal Data API across 50+ datasets and roughly 180 data tables (no API key required) for federal financial data on national debt, government spending, revenue, interest rates, exchange rates, and savings bonds

## Turkish Academia — `turkish-academia` (13)

- **`alterlab-akademik-tesvik`** — Computes the annual Turkish academic-incentive (akademik teşvik) score for Devlet (state) university öğretim elemanı (academic staff) from a classified activity list, applying the verified Akademik Teşvik Ödeneği Yönetmeliği (2018/11834) Faaliyet Hesaplama Tablosu headline puanları (Proje 20, Araştırma 15, Yayın 30, Patent 30, Atıf 30, Tebliğ 20, Ödül 20) with the k (author-count), p (Q1 1/Q2 0.8/Q3 0.5/Q4 0.25), and r (project-role) coefficients via türü puanı = Σ(faaliyet oranları) × headline (MADDE 8/2), then enforcing the per-type headline ceilings, the 100 cap (MADDE 8/3), and the net-30 payment gate (MADDE 10/3) in a deterministic scripts/tesvik_score.py
- **`alterlab-aperta`** — Drives TÜBİTAK Açık Bilim Politikası (Open