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• 18 hours ago last updated

1. ▌
   Tooluniverse Binder Discovery · mims-harvard bundle

   Discover novel small-molecule binders for protein targets using structure-based and ligand-based screening. Covers druggability assessment, known-ligand mining (ChEMBL, BindingDB), similarity expansion, ADMET filtering, and synthesis feasibility. Use for hit identification, virtual screening, target-to-compounds workflows, and lead-finding before commit-to-medchem.
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   Tooluniverse Disease Research · mims-harvard bundle

   Generate comprehensive disease research reports covering genetics (causal genes, GWAS, OMIM), pathways (Reactome, KEGG), drugs (existing therapies, repurposing candidates), clinical trials, epidemiology (prevalence, incidence), and phenotypes (HPO). Use for full disease overviews, comprehensive disease characterization, and orphan/rare-disease profiling.
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   Tooluniverse Drug Repurposing · mims-harvard bundle

   Identify drug repurposing candidates via target-based, compound-based, and disease-based strategies. Combines drug-target-disease network reasoning with mechanism rationale, clinical-trial precedent, and patent/regulatory feasibility. Use for hypothesis-generating repurposing for orphan diseases, finding existing drugs for new indications, and prioritizing candidates by evidence and feasibility.
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4. ▌
   Tooluniverse Gwas Finemapping · mims-harvard bundle

   Statistical fine-mapping of GWAS loci using credible sets (SuSiE, FINEMAP) and locus-to-gene scoring (Open Targets L2G). Identifies likely causal variants and target genes — distinct from positional 'nearest gene' which is often wrong. Use for prioritizing causal variants at GWAS hits, comparing fine-mapping methods, and converting lead SNPs to target genes.
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5. ▌
   Tooluniverse Pharmacogenomics · mims-harvard

   Pharmacogenomics (PGx) research — drug-gene interactions (CPIC, PharmGKB), CPIC dosing guidelines, variant-drug-response associations, ethnic-allele-frequency considerations, and metabolizer-status scoring. Use for PGx-informed dosing recommendations, CYP/HLA pharmacogenomic allele interpretation, and clinically-actionable PGx report generation.
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6. ▌
   Tooluniverse Pharmacokinetics · mims-harvard bundle

   Pharmacokinetic (PK) analysis of concentration-time data — non-compartmental analysis (NCA) for Cmax, Tmax, AUC (0-t and 0-∞), terminal half-life, clearance (CL), volume of distribution (Vd), MRT, and absolute bioavailability (F). Also one-compartment fitting. Use when you have plasma/serum drug concentrations over time after a dose and need PK parameters, or to compute bioavailability from IV + oral AUCs. NOT for ADMET property prediction from structure (use tooluniverse-admet-prediction).
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7. ▌
   Tooluniverse Variant Analysis · mims-harvard bundle

   VCF and variant analysis — parsing, annotation, classification (synonymous, missense, frameshift, stop_gained), VAF filtering, coding vs non-coding categorization, multi-condition variant comparison. Use for VCF parsing, variant fraction calculations (denominator = coding subset only, NOT all variants), and per-sample mutation profiling.
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8. ▌
   Tooluniverse Chemical Sourcing · mims-harvard

   Find commercial sources for chemical compounds — PubChem/ChEMBL identity resolution then vendor catalog search across ZINC, Enamine, eMolecules, Mcule. Compares pricing, availability, and identifies purchasable analogs when an exact compound is not in stock. Use for chemical procurement, virtual library curation, and 'where can I buy X' questions for synthesis planning.
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9. ▌
   Tooluniverse Dataset Discovery · mims-harvard

   Find and evaluate research datasets for any scientific question. Maps research questions to required study designs (longitudinal vs cross-sectional, observational vs experimental, single-cohort vs multi-cohort). Use when the user asks 'find data about X', 'where can I get data on Y', or needs a specific cohort/survey/repository. Covers GEO, ArrayExpress, dbGaP, NHANES, UK Biobank, ClinicalTrials.gov, GWAS Catalog, and 30+ scientific repositories.
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10. ▌
    Tooluniverse Kegg Disease Drug · mims-harvard

    KEGG-based disease-drug-variant network research. Connects diseases to causal genes, drugs to molecular targets, and variants to pathways using KEGG's editorially curated databases (KEGG Disease, Drug, Network, Variant, Pathway). Use for drug repurposing via shared pathways, mechanistic disease-gene-drug networks, and pathway-based target discovery. Distinguishes direct (binding) vs indirect (pathway co-membership) drug-target relationships.
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11. ▌
    Tooluniverse Organic Chemistry · mims-harvard bundle

    Organic chemistry reasoning guide for reaction product prediction, mechanism analysis (electrophilic/nucleophilic substitution, addition, elimination, pericyclic, radical), and spectroscopy interpretation (1H/13C NMR, IR, MS). Reasons from first principles (electron flow, kinetic vs thermodynamic) rather than pattern-matching named reactions. Use for organic synthesis problems and mechanism explanations.
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12. ▌
    Tooluniverse Pharmacovigilance · mims-harvard bundle

    Drug safety and adverse event analysis — FAERS spontaneous-report mining, FDA black-box warnings, signal detection (PRR, ROR, IC), risk factors by demographic/comorbidity, and label change tracking. Use for post-market safety surveillance, AE signal investigation, drug-AE association strength scoring, and pharmacovigilance reports.
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13. ▌
    Tooluniverse Sequence Analysis · mims-harvard bundle

    Biological sequence analysis — gene/protein sequence retrieval (NCBI, Ensembl, UniProt), nucleotide/protein search, ortholog discovery, and FASTQ QC + alignment workflows (Trimmomatic, BWA, samtools, coverage depth). Use for sequence retrieval, sequence comparison, FASTQ QC analysis, and read alignment pre-processing.
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14. ▌
    Setup Cell2location Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the cell2location ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
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15. ▌
    Tooluniverse Antigravity Plugin · mims-harvard

    Install, set up, verify, update, pin, uninstall, or troubleshoot the ToolUniverse plugin on Google Antigravity (AGY / Antigravity IDE / Antigravity 2.0). ALWAYS consult this skill for any of those — don't answer from memory, because the exact CLI name (agy), the "agy plugin install <path>" flow, the uvx tooluniverse MCP server, and the API-key env vars are easy to get wrong. Use it whenever someone wants to get ToolUniverse (or "the 1000+ scientific tools" / "the harvard tools") working on Antigravity, says the Antigravity plugin or its tools/skills won't load, hits a uvx or MCP-server startup error, asks how Antigravity updates it, wants to pin or remove it, or finds it running an old tool version. Not for the Codex plugin (use tooluniverse-codex-plugin) or Claude Code plugin (use tooluniverse-claude-code-plugin), for running research with the tools, or for authoring new tools or skills.
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16. ▌
    Tooluniverse Claude Code Plugin · mims-harvard

    Install the ToolUniverse Claude Code plugin in one step — provides MCP server with 1000+ scientific tools, 120+ research skills, slash commands, hooks, and the research agent. Use for first-time plugin install, troubleshooting plugin not loading, verifying MCP server connection, listing API key requirements, or configuring auto-update.
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17. ▌
    Tooluniverse Gwas Trait To Gene · mims-harvard bundle

    Discover causal genes for diseases/traits from GWAS data using Open Targets L2G (locus-to-gene) scoring — integrates eQTL, chromatin interaction, and distance evidence. Use for trait-to-gene mapping, drug-target hypothesis generation from GWAS, and replacing the 'nearest gene' heuristic with multi-evidence L2G scores.
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18. ▌
    Tooluniverse Hla Immunogenomics · mims-harvard

    HLA gene-family analysis and MHC-peptide binding for transplant compatibility, vaccine epitope coverage, and cancer immunotherapy. Uses IMGT (HLA polymorphism), IEDB (epitope-MHC binding), UniProt (annotation), DGIdb (druggability). Use for HLA typing/imputation review, vaccine HLA coverage, and immunotherapy prediction biomarkers (HLA-LOH, neoantigen presentation).
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19. ▌
    Tooluniverse Infectious Disease · mims-harvard bundle

    Rapid pathogen characterization and drug repurposing for outbreaks. Combines pathogen genomics (NCBI, BVBRC), host immune response (IEDB), drug-target databases (ChEMBL, DGIdb), and literature surveillance (PubMed/EuropePMC). Use for emerging-pathogen profiling, antiviral candidate identification, and outbreak intelligence reporting.
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20. ▌
    Tooluniverse Precision Oncology · mims-harvard bundle

    Cancer treatment recommendations from molecular profile (mutations + cancer type + biomarkers) — FDA-approved + investigational therapies, resistance mechanisms, matching clinical trials, prognosis. Uses CIViC, ClinVar, OpenTargets, ClinicalTrials.gov. Use for tumor-board treatment recommendations, evidence-tiered actionability assessment, and FDA-precedent-driven therapy selection.
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21. ▌
    Tooluniverse Stem Cell Organoid · mims-harvard

    Stem cell, iPSC, and organoid research — pluripotency markers, differentiation protocol pathways, lineage commitment factors, organoid model selection. Use for iPSC characterization, differentiation protocol design via developmental-pathway recapitulation, and organoid-model selection for disease modeling.
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22. ▌
    Setup Immune Compass Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the immune COMPASS ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
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23. ▌
    Tooluniverse Cell Line Profiling · mims-harvard bundle

    Cancer cell-line selection and profiling for experimental model choice. Cross-references DepMap, Cellosaurus, COSMIC, PharmacoDB to deliver identity verification, mutation/CNV profile, gene dependencies, drug sensitivities, and druggable targets. Use to answer 'which cell line should I use for studying gene X?' or 'is this cell line a good model for cancer Y?'. Outputs ranked recommendations with rationale, growth characteristics, and known pitfalls.
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24. ▌
    Tooluniverse Clinical Guidelines · mims-harvard bundle

    Search and retrieve clinical practice guidelines from 12+ authoritative sources — NICE, WHO, NCCN, AHA, ADA, SIGN, USPSTF, IDSA, NIH consensus, ESMO/ESC/EASL European societies, and US specialty associations. Use for evidence-graded treatment recommendations, dosing protocols, screening guidance, and authoritative-source-prioritized clinical guidance (NICE/WHO ranked above society guidelines).
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25. ▌
    Tooluniverse Electron Microscopy · mims-harvard

    Search and analyze electron microscopy data — cryo-EM density maps (EMDB), fitted atomic models (PDB), raw micrograph datasets (EMPIAR), and cryo-electron tomography volumes (CryoET Data Portal). Use for finding 3D structural data on a protein/complex, comparing experimental EM resolution to AlphaFold confidence, and accessing raw EM data for re-processing.
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26. ▌
    Tooluniverse Gwas Drug Discovery · mims-harvard bundle

    Transform GWAS signals into drug targets and repurposing opportunities. Connects GWAS-significant loci to causal genes via fine-mapping/eQTL, then to druggable proteins via DGIdb/OpenTargets, then to existing drugs via ChEMBL. Use for GWAS-to-target hypothesis generation, druggable-fraction analysis of disease loci, and human-genetics-validated drug-repurposing prioritization.
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27. ▌
    Tooluniverse Gwas Study Explorer · mims-harvard bundle

    Compare GWAS studies, perform meta-analyses across cohorts, and assess signal replication. Uses GWAS Catalog metadata, study-level statistics, and cross-cohort comparison. Use for evaluating GWAS reproducibility for a trait, meta-analysis sample size and effect-size aggregation, and detecting study heterogeneity (population, design, ancestry).
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28. ▌
    Tooluniverse Microbiome Research · mims-harvard

    Microbiome research using MGnify, GTDB, ENA, OLS (ENVO biomes), and EuropePMC. Covers study discovery, taxonomic profiling, host-microbe interaction analysis, and biome-by-condition queries. Use for microbiome study selection, organism-environment associations, and clinical-microbiome literature review. Distinct from analytical workflow (use tooluniverse-metagenomics-analysis for that).
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29. ▌
    Tooluniverse Population Genetics · mims-harvard bundle

    Population genetics analysis — allele frequencies (gnomAD, 1000 Genomes), Hardy-Weinberg equilibrium testing, Fst between populations, GWAS associations, evolutionary constraint scores. Use for cross-population variant comparison, ancestry-aware allele frequency lookups, and population-level evolutionary analysis.
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30. ▌
    Tooluniverse Proteomics Analysis · mims-harvard bundle

    Mass-spec proteomics analysis — protein identification, quantification (LFQ, TMT, iTRAQ), differential expression (tumor vs normal, treatment vs control), PTM identification, and pathway enrichment on protein lists. Use when you have proteomics MS output, asking about protein abundance differences, or doing systems-level proteomic interpretation.
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31. ▌
    Tooluniverse Regulatory Genomics · mims-harvard

    Transcription factor binding, cis-regulatory elements (cCREs), chromatin accessibility, and regulatory annotation using JASPAR (motifs), ENCODE (cCREs, ChIP-seq), RegulomeDB (regulatory variant scoring), UCSC — plus sequence-based deep-learning prediction of regulatory activity and non-coding variant effects (AlphaGenome, Enformer, Borzoi, ChromBPNet, Evo 2). Use for regulatory element annotation, TF-binding-site prediction, regulatory-region functional impact assessment, and predicting how a non-coding variant or a raw DNA sequence affects expression/chromatin/accessibility. Use this whenever a user asks what regulates a gene, whether a SNP hits a regulatory element, or to predict a non-coding variant's functional effect from sequence.
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32. ▌
    Setup Expert Feedback Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the Human expert feedback ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
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33. ▌
    Tooluniverse Antibody Engineering · mims-harvard bundle

    Therapeutic antibody engineering and optimization, lead-to-clinical-candidate. Covers sequence humanization (germline alignment, framework retention), affinity maturation, developability (aggregation, stability, PTMs), structure modeling (AlphaFold/PDB CDR analysis), immunogenicity prediction, and manufacturing feasibility. Use for biologic-drug optimization, mAb design review, biosimilar engineering, and clinical-precedent comparison.
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34. ▌
    Tooluniverse Cancer Genomics Tcga · mims-harvard

    TCGA/GDC cancer genomics analysis — cohort construction, clinical metadata retrieval, somatic mutation frequencies, survival analysis, and multi-omics integration. Use for TCGA-BRCA-style cohort studies, mutation prevalence by cancer type, survival-by-mutation analysis, and pan-cancer driver discovery. Always cancer-type-specific (don't use pan-cancer counts without cohort context).
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35. ▌
    Tooluniverse Comparative Genomics · mims-harvard bundle

    Cross-species gene comparison and ortholog analysis. Integrates Ensembl Compara orthologs, NCBI Gene, UniProt, OLS, Monarch, and OpenTargets to identify orthologs, paralogs, sequence conservation, functional conservation across species, and lineage-specific gene gains/losses. Use for phylogenetic gene tracing, model-organism mapping, and evolutionary-genomics queries.
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36. ▌
    Tooluniverse Ecology Biodiversity · mims-harvard

    Ecology, biodiversity, and conservation biology research — species identification (GBIF, NCBI Taxonomy), invasive species impact, ecosystem dynamics, conservation status (IUCN), niche ecology. Use for biodiversity questions, species comparison, invasion biology, conservation prioritization, and ecology-related literature search.
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37. ▌
    Tooluniverse Metabolomics Pathway · mims-harvard

    Metabolomics pathway analysis — metabolite identification (HMDB, KEGG, ChEBI), pathway mapping (Reactome, KEGG, MetaCyc), disease associations, enzyme/gene linkage. Use for metabolite-to-pathway-to-disease connections, BridgeDb-based ID conversion, and integrating metabolomics with gene-level pathway analyses.
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38. ▌
    Tooluniverse Network Pharmacology · mims-harvard bundle

    Compound-target-disease network construction and analysis for drug repurposing, polypharmacology discovery, and multi-target drug design. Uses STRING, BioGRID, ChEMBL, DGIdb, OMIM, OpenTargets. Use for off-target effect prediction, network-based drug repurposing, and identifying molecules with desired multi-target profile.
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39. ▌
    Tooluniverse Polygenic Risk Score · mims-harvard bundle

    Build and interpret polygenic risk scores (PRS) for complex diseases using GWAS summary statistics. Covers PRS construction (clumping/thresholding, PRS-CS), validation in independent cohorts, ancestry-aware adjustment, and clinical interpretation (population-relative risk, not absolute prediction). Use for PRS-based risk stratification.
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40. ▌
    Tooluniverse Protein Interactions · mims-harvard bundle

    Protein-protein interaction (PPI) network analysis — STRING (predicted + experimental), BioGRID (curated), SASBDB (small-angle scattering). Distinguishes physical interactions (binding) from functional associations (co-expression, co-regulation). Use for interactome queries, complex partner identification, and pathway-level interaction analysis.
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41. ▌
    Tooluniverse Statistical Modeling · mims-harvard bundle

    Statistical modeling — linear/logistic/ordinal/Poisson regression, ANOVA, Kruskal-Wallis, chi-square, Mann-Whitney, Cox survival, spline fits (R `ns()`), odds ratios, Cohen's d, F-statistic, p-value computation. Specializes in clinical-trial AE analysis (SDTM DM/AE), severity ordinal regression, and per-feature stat workflows.
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42. ▌
    Devtu Github · mims-harvard bundle

    GitHub workflow for ToolUniverse - push code safely by moving temp files, activating pre-commit hooks, running tests, and cleaning staged files. Use when pushing to GitHub, fixing CI failures, or cleaning up before commits.
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43. ▌
    Tooluniverse · mims-harvard bundle

    ToolUniverse plugin router. STEP 1 BEFORE ANY ANALYSIS: if the data folder contains `*_executed.ipynb`, run `tu run read_executed_notebook '{"data_folder":"<path>","search":"<keyword>"}'` to extract its cell outputs and apply EVERY filter/sample-exclusion the notebook used — even when the question says 'Using DESeq2/Run X/Compute Y' (this describes the METHOD the notebook used, not a request to rerun). The notebook's cell outputs are the only published authoritative answers; reimplementing or reading stale pre-computed CSVs in the data folder produces different numbers because of outlier-sample removal, library version, and filter steps you don't see by skimming. STEP 2 routing — pick a sub-skill name from this exact list (never invent): tooluniverse-rnaseq-deseq2 (RNA/miRNA-seq DE, correlation, PCA, clustering, dispersion), tooluniverse-gene-enrichment (GO/KEGG/Reactome/GSEA/pathway enrichment), tooluniverse-statistical-modeling (regression, ANOVA, ordinal/logistic, chi-square, correlation, power), toolunive
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44. ▌
    Devtu Fix Tool · mims-harvard bundle

    Fix failing ToolUniverse tools by diagnosing test failures, identifying root causes, implementing fixes, and validating solutions. Use when ToolUniverse tools fail tests, return errors, have schema validation issues, or when asked to debug or fix tools in the ToolUniverse framework.
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45. ▌
    Tooluniverse Sdk · mims-harvard bundle

    Build AI scientist systems with the ToolUniverse Python SDK for scientific research. Covers the 3 calling patterns (`tu.run` portable dict API, `tu.tools.X` function API, direct class instantiation), tool loading, batch execution, MCP server integration, and embedding-based tool search. Use for SDK programming, custom tool composition, benchmarking pipelines, and integrating ToolUniverse into research workflows.
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46. ▌
    Devtu Self Evolve · mims-harvard bundle

    Orchestrate the full ToolUniverse self-improvement cycle: discover APIs, create tools, test with researcher personas, fix issues, optimize skills, and push via git. References and dispatches to all other devtu skills. Use when asked to: run the self-improvement loop, do a debug/test round, expand tool coverage, improve tool quality, or evolve ToolUniverse.
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47. ▌
    Devtu Docs Quality · mims-harvard bundle

    TOP PRIORITY skill — find and immediately fix or remove every piece of wrong, outdated, or redundant information in ToolUniverse docs. Wrong code, broken links, incorrect counts, and overlapping instructions must be fixed or removed — never left in place. Runs five phases: (D) static method scan, (C) live code execution, (A) automated validation, (B) ToolUniverse audit, (E) less-is-more simplification. Core philosophy: each concept appears exactly once; remove don't add; no emojis; single setup entry point. Use when reviewing docs, before releases, after API changes, or when asked to audit, fix, or simplify documentation.
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48. ▌
    Setup Tooluniverse · mims-harvard bundle

    Install and configure ToolUniverse for any use case — MCP server (chat-based), CLI (command line with 9 subcommands), or Python SDK (Coding API with 3 calling patterns). Covers uv/uvx setup, MCP configuration for 12+ AI clients (Cursor, Claude Desktop, Windsurf, VS Code, Codex, Gemini CLI, Trae, Cline, etc.), full CLI reference (tu list/grep/find/info/run/test/status/build/serve), Coding API quickstart, agentic tools, code executor, API key walkthrough, skill installation, and upgrading. Use when user asks how to set up ToolUniverse, which access mode to use (MCP vs CLI vs SDK), configuring MCP servers, using the CLI, troubleshooting installation, upgrading, or mentions installing ToolUniverse or setting up scientific tools. Also triggers for "how do I use ToolUniverse", "what's the best way to access tools", "command line", "tu command", "coding API", "tu build".
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49. ▌
    Devtu Optimize Skills · mims-harvard bundle

    Optimize ToolUniverse skills for better report quality, evidence handling, and user experience. Apply patterns like tool verification, foundation data layers, disambiguation-first, evidence grading, quantified completeness, and report-only output. Use when reviewing skills, improving existing skills, or creating new ToolUniverse research skills.
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50. ▌
    Setup Esm Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the ESM ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
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51. ▌
    Tooluniverse Cs Setup · mims-harvard bundle

    Install or update ToolUniverse in Claude Science — create the conda env, install the tooluniverse pip package, and (re)build the tooluniverse-research skill by fetching the current workflow library from GitHub. Use for first-time setup, upgrading the ToolUniverse version, refreshing the bundled workflows after an upstream release, or reinstalling on a new machine.
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52. ▌
    Setup Ldsc Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the LDSC ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
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53. ▌
    Setup Milo Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the Milo ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
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54. ▌
    Setup Mofa Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the MOFA+ ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
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55. ▌
    Setup Paga Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the PAGA ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
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56. ▌
    Setup Scvi Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the scVI ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
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57. ▌
    Devtu Benchmark Harness · mims-harvard bundle

    Continuous improvement system for ToolUniverse tools, skills, and plugin. Run benchmarks, diagnose failures, route fixes to devtu skills, retest. Use after skill optimization, tool additions, or as regression check.
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58. ▌
    Setup Boltz Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the Boltz-2 ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
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59. ▌
    Setup Liana Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the LIANA ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
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60. ▌
    Setup Macs3 Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the MACS3 ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
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61. ▌
    Tooluniverse Immunology · mims-harvard

    Immunology research workflows: antibody-antigen interactions, T/B cell repertoire, MHC/HLA binding prediction, autoimmune disease genetics, vaccine epitope mapping. Uses IEDB, IMGT, SAbDab, UniProt. Use for adaptive immunity questions, immune response analysis, antibody/TCR/BCR characterization, immunogenicity prediction, and immune-pathway-to-disease mapping.
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62. ▌
    Tooluniverse Lipidomics · mims-harvard

    Lipid analysis and lipid-disease associations using LIPID MAPS classification, HMDB metabolite data, KEGG/Reactome lipid pathways (sphingolipid, eicosanoid, steroid, fatty acid), and PubChem chemical info. Use for lipid identification, lipid metabolism pathway mapping, and lipid-associated disease analysis (cardiovascular, diabetes, NAFLD).
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63. ▌
    Tooluniverse Toxicology · mims-harvard

    Drug and chemical toxicity assessment via adverse outcome pathways (AOPs), real-world FAERS adverse event signals, FDA labels, and toxicogenomic associations. Triangulates molecular initiating event to cellular outcome to organ-level toxicity to clinical adverse event. Use for hepatotoxicity/cardiotoxicity/nephrotoxicity prediction and toxicology reports.
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64. ▌
    Setup Borzoi Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the Borzoi ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
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65. ▌
    Setup Scanvi Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the scANVI ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
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66. ▌
    Setup Scvelo Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the scVelo ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
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67. ▌
    Tooluniverse Custom Tool · mims-harvard bundle

    Add custom local tools to ToolUniverse alongside the 1000+ built-in tools. Covers JSON-config tools (simplest, no code), Python class tools (REST/SOAP/GraphQL APIs, computational logic), and best-practices for return schemas. Use for wrapping new APIs, adding domain-specific computations, or contributing tools to the registry.
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68. ▌
    Tooluniverse Epigenomics · mims-harvard bundle

    Genomics and epigenomics analysis: DNA methylation (CpG, 5mC, 5hmC, bisulfite, RRBS), m6A RNA modification (MeRIP-seq), ChIP-seq peaks, ATAC-seq accessibility, histone modifications, chromatin state, multi-omics integration. Combines pandas/scipy/pysam computation with ToolUniverse annotation tools. Use for genome-wide epigenomic statistics, methylation analysis, and chromatin-genome integration.
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69. ▌
    Tooluniverse Self Review · mims-harvard bundle

    Review existing work against the user's actual goal and surface evidence-backed strengths, gaps, risks, and next fixes. Use when asked to eval, evaluate, review, assess, or check current/this/my/our work; decide whether a task is complete; build a definition-of-done checklist or rubric; or perform grading, LLM-as-judge, Qworld, or RET evaluation. Treat plain eval/review requests as qualitative: resolve "current work" from the conversation, artifacts, files, or diff, and never assign numeric scores unless the user explicitly requests scores, grades, points, ratings, weighted criteria, Qworld, or RET. Do not use for implementing automated eval suites, tests, graders, or benchmarks.
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70. ▌
    Tooluniverse Single Cell · mims-harvard bundle

    Single-cell RNA-seq analysis with scanpy/anndata — h5ad data loading, scRNA-seq quality control and QC gating (n_genes_by_counts, total_counts, mitochondrial percent / pct_counts_mt, pct_counts_ribo, doublet detection with Scrublet/scDblFinder, ambient RNA / SoupX awareness, empty-droplet filtering, MAD-based thresholds), normalization, dimensionality reduction (PCA, UMAP, t-SNE), clustering (Leiden, Louvain), marker gene identification, cell-type annotation, pseudotime/trajectory analysis. Use for any scRNA-seq workflow, including deciding which cells to filter, flag, or investigate before downstream analysis.
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71. ▌
    Create Tooluniverse Skill · mims-harvard bundle

    Create high-quality ToolUniverse skills following test-driven, implementation-agnostic methodology.
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72. ▌
    Setup Harmony Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the Harmony ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
    0
    installs
73. ▌
    Setup Singler Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the SingleR ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
    0
    installs
74. ▌
    Setup Squidpy Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the Squidpy ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
    0
    installs
75. ▌
    Setup Tangram Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the Tangram ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
    0
    installs
76. ▌
    Tooluniverse Codex Plugin · mims-harvard

    Install, set up, verify, update, pin, uninstall, or troubleshoot the ToolUniverse plugin on OpenAI Codex. ALWAYS consult this skill for any of those — don't answer from memory, because the exact marketplace name (mims-harvard/ToolUniverse), the "codex plugin marketplace add" then "codex plugin add -m tooluniverse" flow, Codex's startup auto-upgrade behavior, the uvx tooluniverse MCP server, and the API-key env vars are easy to get wrong. Use it whenever someone wants to get ToolUniverse (or "the 1000+ scientific tools" / "the harvard tools") working on Codex, says the Codex plugin or its tools/skills won't load, hits a uvx or MCP-server startup error, asks how Codex updates it, wants to pin or remove it, or finds it running an old tool version — even if they never say the word "plugin". Not for the Claude Code plugin (use tooluniverse-claude-code-plugin), for running research with the tools, or for authoring new tools or skills.
    0
    installs
77. ▌
    Tooluniverse Drug Synergy · mims-harvard bundle

    Drug-combination synergy analysis — quantify whether two drugs together are synergistic, additive, or antagonistic using the standard reference models (Bliss independence, HSA / highest single agent, Loewe additivity, ZIP, and the Chou-Talalay Combination Index). Use when you have measured single-drug and combination effects (inhibition/viability) and need a synergy score. Explains which model to use, what data each one needs, and how to read the score. NOT for looking up pre-computed synergy in a database (use the SYNERGxDB tool / cell-line-profiling skill).
    0
    installs
78. ▌
    Tooluniverse Metabolomics · mims-harvard bundle

    Metabolomics research — metabolite identification, study analysis, and database searches across HMDB, MetaboLights, Metabolomics Workbench, KEGG. Use for annotating mass-spec features to known metabolites, finding metabolomics studies of a disease, and structured metabolomics research reports with metabolite-pathway mapping.
    0
    installs
79. ▌
    Tooluniverse Neuroscience · mims-harvard

    Neuroscience research workflows: neuroanatomy, neural circuits, neurotransmitter biology, neurological/psychiatric disease genetics, neural-protein function. Uses Allen Brain Atlas, WormBase (C. elegans connectome), UniProt for neural proteins, PubMed for primary literature. Use for brain-region biology, neural development, neurodegeneration mechanisms (Alzheimer's, Parkinson's, ALS), and synaptic-protein characterization.
    0
    installs
80. ▌
    Host And Share Remote Tool · mims-harvard bundle

    Host, validate, and privately share a user's own model, Python function, workflow, or existing Streamable HTTP MCP endpoint through ToolUniverse Platform. Use when turning a local CPU/GPU workload or lab endpoint into a stable TU remote tool, diagnosing its setup, or preparing it for controlled sharing.
    0
    installs
81. ▌
    Setup Cellrank Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the CellRank ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
    0
    installs
82. ▌
    Setup Enformer Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the Enformer ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
    0
    installs
83. ▌
    Setup Monocle3 Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the Monocle 3 ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
    0
    installs
84. ▌
    Setup Pinnacle Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the PINNACLE ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
    0
    installs
85. ▌
    Setup Scrublet Remote Tool · mims-harvard bundle

    Set up, launch, validate, and troubleshoot the Scrublet ToolUniverse remote tool and optionally relay it through ToolUniverse Connect. Use when deploying or auditing this implementation.
    0
    installs
86. ▌
    Tooluniverse Dose Response · mims-harvard bundle

    Dose-response / concentration-response curve fitting — IC50, EC50, Hill slope, Emax/Emin efficacy, and relative potency from paired concentration vs response data (enzyme/cell assays, drug screening, agonist/antagonist pharmacology). Fits the 4-parameter logistic (Hill sigmoidal) model. Use when you have concentrations + responses and need a potency value, to compare two compounds' potency, or to judge curve quality. NOT for image-derived dose-response (use tooluniverse-image-analysis) and NOT for survival/regression (use tooluniverse-statistical-modeling).
    0
    installs
87. ▌
    Tooluniverse Drug Research · mims-harvard bundle

    Comprehensive drug profiling — mechanism, primary/secondary targets, drug interactions, clinical-trial status, adverse events (FAERS), pharmacogenomics, and approval history. Use for full drug investigation reports, 'tell me about drug X' queries, and assembling drug profiles for clinicians, researchers, or regulatory work.
    0
    installs