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Browse reusable Agent Skills, each with a clear purpose and practical guidance.
review-code
Pinpoint 프로젝트 규약에 따라 코드 변경을 리뷰합니다. 커밋 전, PR 리뷰, 또는 코드 품질을 점검할 때 반드시 이 스킬을 사용하세요.
write-test
변경되었거나 테스트가 없는 Pinpoint 프론트엔드 코드에 대한 Jest 테스트를 작성합니다. 훅, 아톰, 유틸리티, 컴포넌트에 테스트가 필요하거나 커버리지를 높여야 할 때 반드시 이 스킬을 사용하세요.
fba-simulator
Run Flux Balance Analysis (FBA) and related constraint-based simulations using COBRApy. Covers standard FBA, parsimonious FBA (pFBA), Flux Variability Analysis (FVA), loopless FBA, gene/reaction knockouts, and carbon source swapping. Outputs flux distributions and CSV files.
flux-analyzer
Analyse FBA flux distributions to extract biological insights. Covers gene essentiality, phenotypic phase planes, flux sampling, pathway-level aggregation, secretion product prediction, and production of publication- quality figures.
gsmm-validator
Validate a COBRApy genome-scale metabolic model for mass/charge balance, stoichiometric consistency, biomass producibility, dead-end metabolites, thermodynamic loops, and GPR rule formatting. Outputs a structured validation report with errors and warnings.
metabolic-study-planner
Plan publishable constraint-based metabolic modelling studies when the user has a broad biological or metabolic-engineering topic but no concrete dataset, organism, model, or hypothesis. Selects feasible BiGG/COBRA models, objectives, perturbations, analyses, metrics, figures, and risk controls before FBA code is generated.
quantum-qiskit
Reference qiskit 2.x patterns for variational quantum machine learning. Covers data-encoding feature maps, variational quantum classifier (VQC) training, variational quantum eigensolver (VQE) for chemistry, matrix-product-state circuits, and noise model integration. Use when writing Python code that imports `qiskit`, `qiskit_aer`, `qiskit_algorithms`, `qiskit_machine_learning`, or `qiskit_nature`.
stat-research-orchestrator
Orchestrate a statistical research pipeline centered on formal problem formulation, method proposal, theoretical analysis, experimental evaluation, comparison, and final result synthesis.
statistical-experimental-evaluation
Design and run statistical experiments that test the formal problem, proposed methods, theoretical predictions, baselines, and ablations.