ultimate-research
Elite multi-agent research orchestration utilizing ref MCP, exa MCP, brave-search MCP, and context7 with parallel execution of deep-research-agent, search-specialist, trend-researcher, and ux-researcher. Use fo...
发现 documentation 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。
Elite multi-agent research orchestration utilizing ref MCP, exa MCP, brave-search MCP, and context7 with parallel execution of deep-research-agent, search-specialist, trend-researcher, and ux-researcher. Use fo...
Systematic approach to conducting research and synthesizing information
Comprehensive discovery before starting any spec or major task. Searches Graphiti, recommends vibe/MCPs, surfaces patterns.
Analyze completed growth experiment results, validate hypotheses, generate insights, and suggest follow-up experiments. Use when experiments are completed, when the user asks about results or learnings, or when...
Coordinates academic research workflow - delegates analysis, correlation, writing, and review tasks to specialist agents
research-designer for evidence-based learning research and evaluation.
Use this skill for comprehensive research tasks requiring deep investigation, multiple source validation, and citation-backed reports. Triggers on keywords like "research", "investigate", "deep dive", "comprehe...
Perform observational constraint (Emergent Constraint, EC) analysis for climate research. Use historical observations to constrain future climate projections from CMIP6 multi-model ensembles, reducing predictio...
This skill should be used when setting up, optimizing, or managing MetaNova NOVA miners on Bittensor Subnet 68 (SN68). Use it for miner configuration, molecular search strategy development, PSICHIC scoring opti...
Capital allocation and exit recycling investigator. Use when working on low-confidence modules like capital allocation and exit recycling.
Analyzes relationships and connections between body systems, identifying root causes and hidden patterns in medical data.
Transforms medical analysis reports into stunning, personalized, data-driven Health Realms using intelligent visualization.
Extracts structured, chart-ready JSON data from medical analysis for visualization, including diagnoses, timeline, prognosis, and supplement schedules.
Agentic medical analyst that explores extracted documents iteratively like a real physician - forming hypotheses, seeking evidence, cross-referencing, and building comprehensive analysis through multiple explor...
Research voids (cognitive gaps, unchartable territories). Daily. Outputs research notes for voids articles.
RFdiffusion3 protein design reference. Use when working with RFD3, contigs, symmetry, hotspots, fixed atoms, RASA conditioning, H-bond conditioning, or Foundry API. Covers all input parameters, design types, an...
BindCraft protein binder design reference. Use when working with AF2 backpropagation, binder design, interface optimization, PyRosetta metrics, design filtering, or comparing with RFdiffusion approaches.
LigandMPNN sequence design reference. Use when working with LigandMPNN, ProteinMPNN, sequence design, amino acid biasing, fixed residues, temperature, side chain packing, or membrane protein design.
Perform comprehensive research using the diffusion research loop - parallel worker agents, iterative gap detection, and structured synthesis. Use when you need thorough, multi-perspective research with citation...
AI-powered research skill with five workflows - chat (single-model conversation), consensus (multi-model synthesis), thinkdeep (systematic investigation), ideate (creative brainstorming), and deep (multi-phase...
python-controlを使用して、メカニカルシステムの状態空間モデルから伝達関数(Bode Plot)を計算・表示する
MCMC convergence diagnostics using CmdStanPy and ArviZ
Create detailed research plans by decomposing structured prompts into subtopics, search strategies, and agent deployment configurations. Extracted from Phase 2 of research-executor for standalone planning capab...
Central Goal-Oriented Action Planning orchestrator that plans and executes clinical analysis pipelines
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。