translational-research
De la autor
Reason about translational research problems in HCLS — especially neurology and hypothesis validation. Use when the user asks to design a validation study, evaluate a target, qualify a biomarker, choose endpoints, critique a preclinical-to-clinical plan, pick a trial design (basket/umbrella/platform), plan multimodal data integration, or assess whether a hypothesis is ready to advance. Triggers include phrases like "validate target", "biomarker context of use", "bench to bedside", "T0/T1/T2/T3/T4", "proof of mechanism", "target engagement", "design a trial for", "preclinical model translates", "imaging-genetics", "is this ready for Phase 2", "mouse results to humans", "GWAS/eQTL/MR", "endpoint selection", "drug repurposing rationale", "fail fast".
Instalare
npx skills add awslabs/hcls-agent-skills --skill translational-research -a claude-code
Se instalează în .claude/skills/translational-research/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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De ce 82
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- biomarker-discoveryawslabs/hcls-agent-skillsReason about biomarker discovery and validation in HCLS — classifying biomarker intent, choosing feature-selection and cross-validation strategies, avoiding leakage, and planning external replication. Use when the user asks to discover, develop, or validate a biomarker; select features from high-dimensional omics or clinical data; design a validation study; choose evaluation metrics; justify sample size; combine multi-omics signals; or assess clinical utility. Triggers include "discover a biomarker", "validate biomarker", "prognostic vs predictive", "feature selection", "LASSO vs elastic net", "nested cross-validation", "data leakage", "C-index", "time-dependent AUC", "decision curve analysis", "external validation cohort", "events per variable", "optimism-corrected", "multi-omics integration", "clinical utility of a biomarker", "is this biomarker ready".Design★ 66
- drug-repurposingawslabs/hcls-agent-skillsReason about drug repurposing strategies in HCLS — choosing between target-based and phenotype-based approaches, evaluating mechanism-of-action overlap, querying drug-gene interaction databases, assessing clinical translatability, and ranking candidates by evidence strength. Use when the user asks to repurpose a drug, find approved drugs for a new indication, evaluate a repurposing candidate, query DGIdb or OpenTargets, assess drug-target interactions, design a repurposing study, rank repurposing evidence, or evaluate translatability of a candidate. Triggers include "drug repurposing", "repurpose", "repositioning", "new indication", "off-label use", "target-based repurposing", "phenotype-based repurposing", "CMap", "L1000", "DGIdb", "OpenTargets", "DrugBank", "ChEMBL", "mechanism of action overlap", "drug-gene interaction", "translatability", "existing safety data", "repurposing evidence hierarchy".Design★ 66
- ml-researcherawslabs/hcls-agent-skillsReason about ML experiment design for healthcare and life sciences data. Use when the user asks to design an ML study, choose a model for clinical/biomedical data, set up cross-validation, pick evaluation metrics, audit fairness, plan a regulatory submission, or critique an ML pipeline on EHR, medical imaging, genomics, molecules, or clinical text. Triggers include "design an ML experiment", "which model for this clinical data", "how should I split", "nested CV", "class imbalance", "AUROC vs AUPRC", "calibration", "decision curve", "net benefit", "TRIPOD+AI", "PROBAST", "CLAIM", "FDA SaMD", "PCCP", "GMLP", "site generalization", "temporal leakage", "scaffold split", "foundation model evaluation", "subgroup fairness", "is this model ready for deployment".DevOps★ 66
- scientific-thinking-biologyAgents365-ai/365-skillsUse when interpreting biological research findings, evaluating life science evidence, analyzing molecular or cellular mechanisms, comparing competing biological hypotheses, designing or critiquing experiments in biology, genetics, genomics, cell biology, immunology, neuroscience, ecology, or any life science domain. Triggers on questions about gene function, pathways, phenotypes, GWAS hits, single-cell data, animal models, clinical translation, evolutionary arguments, or any biology/life science reasoning task.Știință★ 90
- literature-researchfcakyon/phd-skillsUse when the user wants to find related work, survey a research area, identify literature gaps, or discover open-source implementations. Triggers on phrases like "find papers on", "related work", "literature review", "what papers exist", "open source implementation", or "papers with code".Știință★ 433
- web-researchexistential-birds/beagleUse when the user wants web research: gathering cited, multi-angle evidence on a specific question. Triggers on: "research X for me", "do web research on", "look up sources for", "find citations for", "gather evidence on", "what does the web say about X". Also invoked programmatically by other beagle skills (prfaq-beagle Ignition, brainstorm-beagle reference points, strategy-interview context grounding) via the companion contract. Does NOT trigger on codebase lookups ("find this function", "search the repo"), local file search, LLM-as-judge evaluation, or paywalled/auth-gated scraping. Produces a written plan, parallel-subagent findings, and a cited synthesis report on disk — never inline prose, never unsourced claims.Știință★ 84
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