julia-scientific
Julia package equivalents for 137 K-Dense-AI scientific skills. Maps Python bioinformatics, chemistry, ML, quantum, and data science packages to native Julia ecosystem.
发现 tools scientific computing 相关 Skills,比较来源仓库和用途,查看适合你工作流的技能说明。
Julia package equivalents for 137 K-Dense-AI scientific skills. Maps Python bioinformatics, chemistry, ML, quantum, and data science packages to native Julia ecosystem.
Interacting dynamical systems
Chemical Reaction Network topology for generating and analyzing reaction
Layer 5: SDE-Based Learning Analysis via Langevin Dynamics
Coupled oscillators with sinusoidal coupling
OlmoEarth MLX: Spatio-Temporal Earth Intelligence
Strange attractor with sensitive dependence on initial conditions
Kolmogorov complexity as the ultimate intelligence measure. Shortest
Local approximation of nonlinear dynamics
Research technical solutions by searching the web, examining GitHub repos, and gathering evidence. Use when exploring implementation options or evaluating technologies.
Deep analytical investigation mode using Bayesian reasoning, superforecasting techniques, and rigorous hypothesis testing. Combines methods from Kahneman, Tetlock, Peirce, and Feynman. Use when user invokes /in...
Global drug development pipeline tracking by disease, target, mechanism, or company. Use for competitive intelligence, opportunity identification, and trend analysis. Keywords: pipeline, drug development, clin...
Generate comprehensive target profiles including druggability assessment, disease associations, pathway context, and competitive landscape. Use this skill when analyzing drug targets for validation, dossier cr...
Generate comprehensive compound profiles including structure, properties, bioactivity, and development status. Use for drug analysis, SAR studies, and competitive profiling. Keywords: compound, drug, molecule,...
Generate professional drug discovery reports including target dossiers, competitive briefs, and Go/No-Go decision summaries. Use this skill when you need formatted reports for presentations, decision meetings,...
Create interactive HTML artifacts for academic papers using parallel subagent processing. Includes comprehensive pre-submission review checklist for paper quality assurance.
Complex research requiring deeper analysis, multi-step reasoning, and sophisticated source evaluation for technical, academic, or specialized domain queries needing expert-level analysis, high-stakes decisions,...
Systematic research workflow orchestrating multi-source research operations for comprehensive domain investigation. Sequential workflow from web search through GitHub exploration and documentation analysis to r...
Comprehensive research and analysis using Claude (subagents), Gemini CLI, and Codex CLI. Multi-perspective research with cross-verification, iterative refinement, and 100% citation coverage. Use for security an...
Deep research on technical topics using EXA tools with intelligent two-tier caching. Use when user asks to research a topic, investigate best practices, look up information, find patterns, or explore architectu...
Orchestrates life sciences APIs to build knowledge graphs using the Fuzzy-to-Fact protocol, combining MCPs for nodes and curl for edges, then persisting to Graphiti. This skill should be used when the user asks...
Queries protein databases (UniProt, STRING, BioGRID) via curl for protein lookups, protein-protein interactions, functional enrichment analysis, and cross-database ID mapping. This skill should be used when the...
Queries clinical databases (Open Targets, ClinicalTrials.gov) via curl for target-disease associations, target tractability assessment, and clinical trial discovery. This skill should be used when the user asks...
Queries genomic databases (Ensembl, NCBI, HGNC) via curl for gene lookup, variant annotation, orthology, and cross-database ID resolution. This skill should be used when the user asks to "annotate variants", "f...
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。