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Chemistry

Molecular modeling and reactions.

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computational-chemistry

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Deep academic research for antibody design campaigns — target analysis, literature review, prior art search, epitope identification. Uses an 8-phase pipeline with quality gates and persistent memory. Use this skill whenever researching a protein target, starting a new design campaign, investigating prior art, analyzing epitopes, reviewing literature for design strategy, or when the user mentions target research, literature search, or prior art in the context of protein/antibody design.

001TMF

research

computational-chemistry

43

proteus-research

Deep academic research for antibody design campaigns — target analysis, literature review, prior art search, epitope identification. Uses an 8-phase pipeline with quality gates and persistent memory. Use this skill whenever researching a protein target, starting a new design campaign, investigating prior art, analyzing epitopes, reviewing literature for design strategy, or when the user mentions target research, literature search, or prior art in the context of protein/antibody design.

001TMF

research

computational-chemistry

43

boltzgen

Antibody and nanobody binder design using BoltzGen (BoltzGen diffusion + Protenix refolding). Covers entity YAML specification, CLI invocation, protocol selection (nanobody-anything / antibody-anything), MSA modes, and output parsing. Use this skill whenever the user needs to design an antibody or nanobody binder against a protein target.

001TMF

research

computational-chemistry

43

tooluniverse-clinical-trial-matching

AI-driven patient-to-trial matching for precision medicine and oncology. Given a patient profile (disease, molecular alterations, stage, prior treatments), discovers and ranks clinical trials from ClinicalTrials.gov using multi-dimensional matching across molecular eligibility, clinical criteria, drug-biomarker alignment, evidence strength, and geographic feasibility. Produces a quantitative Trial Match Score (0-100) per trial with tiered recommendations and a comprehensive markdown report. Use when oncologists, molecular tumor boards, or patients ask about clinical trial options for specific cancer types, biomarker profiles, or post-progression scenarios.

Zaoqu-Liu

research

computational-chemistry

43

tooluniverse-drug-research

Generates comprehensive drug research reports with compound disambiguation, evidence grading, and mandatory completeness sections. Covers identity, chemistry, pharmacology, targets, clinical trials, safety, pharmacogenomics, and ADMET properties. Use when users ask about drugs, medications, therapeutics, or need drug profiling, safety assessment, or clinical development research.

Zaoqu-Liu

research

computational-chemistry

43

tooluniverse-drug-target-validation

Comprehensive computational validation of drug targets for early-stage drug discovery. Evaluates targets across 10 dimensions (disambiguation, disease association, druggability, chemical matter, clinical precedent, safety, pathway context, validation evidence, structural insights, validation roadmap) using 60+ ToolUniverse tools. Produces a quantitative Target Validation Score (0-100) with GO/NO-GO recommendation. Use when users ask about target validation, druggability assessment, target prioritization, or "is X a good drug target for Y?"

Zaoqu-Liu

research

computational-chemistry

43

tooluniverse-immunotherapy-response-prediction

Predict patient response to immune checkpoint inhibitors (ICIs) using multi-biomarker integration. Given a cancer type, somatic mutations, and optional biomarkers (TMB, PD-L1, MSI status), performs systematic analysis across 11 phases covering TMB classification, neoantigen burden estimation, MSI/MMR assessment, PD-L1 evaluation, immune microenvironment profiling, mutation-based resistance/sensitivity prediction, clinical evidence retrieval, and multi-biomarker score integration. Generates a quantitative ICI Response Score (0-100), response likelihood tier, specific ICI drug recommendations with evidence, resistance risk factors, and a monitoring plan. Use when oncologists ask about immunotherapy eligibility, checkpoint inhibitor selection, or biomarker-guided ICI treatment decisions.

Zaoqu-Liu

research

computational-chemistry

43

tooluniverse-precision-oncology

Provide actionable treatment recommendations for cancer patients based on molecular profile. Interprets tumor mutations, identifies FDA-approved therapies, finds resistance mechanisms, matches clinical trials. Use when oncologist asks about treatment options for specific mutations (EGFR, KRAS, BRAF, etc.), therapy resistance, or clinical trial eligibility.

Zaoqu-Liu

research

computational-chemistry

43

tooluniverse-rare-disease-diagnosis

Provide differential diagnosis for patients with suspected rare diseases based on phenotype and genetic data. Matches symptoms to HPO terms, identifies candidate diseases from Orphanet/OMIM, prioritizes genes for testing, interprets variants of uncertain significance. Use when clinician asks about rare disease diagnosis, unexplained phenotypes, or genetic testing interpretation.

Zaoqu-Liu

research

computational-chemistry

43

stable-baselines3

Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations. Best for single-agent RL with Gymnasium environments. For high-performance parallel training, multi-agent systems, or custom vectorized environments, use pufferlib instead.

Zaoqu-Liu

research

computational-chemistry

43

tooluniverse-adverse-event-detection

Detect and analyze adverse drug event signals using FDA FAERS data, drug labels, disproportionality analysis (PRR, ROR, IC), and biomedical evidence. Generates quantitative safety signal scores (0-100) with evidence grading. Use for post-market surveillance, pharmacovigilance, drug safety assessment, adverse event investigation, and regulatory decision support.

Zaoqu-Liu

research

computational-chemistry

43

tooluniverse-binder-discovery

Discover novel small molecule binders for protein targets using structure-based and ligand-based approaches. Creates actionable reports with candidate compounds, ADMET profiles, and synthesis feasibility. Use when users ask to find small molecules for a target, identify novel binders, perform virtual screening, or need hit-to-lead compound identification.

Zaoqu-Liu

research

computational-chemistry

43

tooluniverse-chemical-safety

Comprehensive chemical safety and toxicology assessment integrating ADMET-AI predictions, CTD toxicogenomics, FDA label safety data, DrugBank safety profiles, and STITCH chemical-protein interactions. Performs predictive toxicology (AMES, DILI, LD50, carcinogenicity), organ/system toxicity profiling, chemical-gene-disease relationship mapping, regulatory safety extraction, and environmental hazard assessment. Use when asked about chemical toxicity, drug safety profiling, ADMET properties, environmental health risks, chemical hazard assessment, or toxicogenomic analysis.

Zaoqu-Liu

research

computational-chemistry

43

tooluniverse-crispr-screen-analysis

Comprehensive CRISPR screen analysis for functional genomics. Analyze pooled or arrayed CRISPR screens (knockout, activation, interference) to identify essential genes, synthetic lethal interactions, and drug targets. Perform sgRNA count processing, gene-level scoring (MAGeCK, BAGEL), quality control, pathway enrichment, and drug target prioritization. Use for CRISPR screen analysis, gene essentiality studies, synthetic lethality detection, functional genomics, drug target validation, or identifying genetic vulnerabilities.

Zaoqu-Liu

research

computational-chemistry

42

madgraph-simulator

Run MadGraph5_aMC@NLO event generation for particle physics simulations via Magnus cloud. Triggers when the user wants to generate Monte Carlo events, simulate collider processes, or run MadGraph5. Supports Pythia8 parton shower and Delphes detector simulation.

HET-AGI

research

computational-chemistry

41

odin

Search memory — sends Huginn (quick grep) first, then Munin (deep agent search) if needed

acostanzo

research

computational-chemistry

40

superpowers-lab

Lab environment for Claude superpowers

benjaminasterA

research

computational-chemistry

40

embedding-strategies

Select and optimize embedding models for semantic search and RAG applications. Use when choosing embedding models, implementing chunking strategies, or optimizing embedding quality for specific dom...

benjaminasterA

research

computational-chemistry

40

azure-ai-anomalydetector-java

Build anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered monitoring.

benjaminasterA

research

computational-chemistry

40

peer-reviewer

Simulate peer review by constructing reviewer personas from Zotero sources. Identifies relevant perspectives, retrieves full texts, builds reviewer profiles, and generates focused reviews on theory/methods and findings.

nealcaren

research

computational-chemistry

40

promptfoo

LLM red teaming and security testing — automated vulnerability scanning for AI agents, RAGs, and LLM pipelines. Covers prompt injection, jailbreaks, data leaks, PII exposure, and 50+ vulnerability types.

InugamiDev

research

computational-chemistry

39

imaging-data-commons

Query and download public cancer imaging data from NCI Imaging Data Commons using idc-index. Use for accessing large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Query by metadata, visualize in browser, check licenses.

lingxling

research

computational-chemistry

39

rowan

Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.

lingxling

research

computational-chemistry

39

fda-database

Query openFDA API for drugs, devices, adverse events, recalls, regulatory submissions (510k, PMA), substance identification (UNII), for FDA regulatory data analysis and safety research.

lingxling

research

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