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Skills IA tools scientific computing

Découvrez les skills tools scientific computing, comparez leurs dépôts et consultez leurs instructions.

Catégories: tools scientific computing

241–264 sur 823

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Explorer

GitHub

adaptive-rejection-sampler

letta-ai

Guidance for implementing adaptive rejection sampling (ARS) algorithms for generating random samples from log-concave probability distributions. This skill should be used when tasks involve implementing ARS, re...

GitHub

mcmc-sampling-stan

letta-ai

Guide for performing Markov Chain Monte Carlo (MCMC) sampling using RStan or PyStan. This skill should be used when implementing Bayesian statistical models, fitting hierarchical models, working with Stan model...

GitHub

bn-fit-modify

letta-ai

Guidance for Bayesian Network DAG structure recovery, parameter learning, and causal intervention tasks. This skill should be used when tasks involve recovering DAG structure from observational data, learning B...

GitHub

lobster-bioinformatics

the-omics-os

Run bioinformatics analyses using Lobster AI - single-cell RNA-seq, bulk RNA-seq, literature mining, dataset discovery, quality control, and visualization. Use when analyzing genomics data, searching for papers...

GitHub

data-synthesis

HyunjunJeon

Synthesize findings from multiple research sources into coherent insights. Use when combining data from different sub-agents or research threads.

GitHub

hypothesis-testing-engine

OneWave-AI

Take any claim and design + execute a complete research protocol to test it. Apply scientific method automatically: design study, gather data, run analysis, provide verdict with confidence level.

GitHub

weak-signal-synthesizer

OneWave-AI

Identify EMERGING trends by connecting dots across unrelated sources. Monitor niche communities, academic research, GitHub, patents, funding, regulatory changes. Predict what will trend in 3-6 months based on w...

GitHub

argus-research-analyst

francomascareloai

ARGUS NANO v2.1 - Compact research skill for context-limited sessions (~3KB). FOCO: Triangulacao (Academico + Pratico + Empirico), validacao de claims, busca multi-fonte com niveis de confianca. DROID: argus-...

GitHub

genome-analyzer

artwist-polyakov

Анализирует генетические данные пользователя из VCF файла. Используй когда пользователь спрашивает о своей генетике, наследственных признаках, предрасположенностях, метаболизме веществ (кофеин, алкоголь, лекарс...

GitHub

data-quality-standards

ilyasibrahim

Data quality validation rules, quality metrics, and acceptance criteria for Somali dialect classifier datasets. Covers duplicate detection, language filtering, quality scoring, and validation protocols. Auto-in...

GitHub

research-analyst

zenobi-us

Expert research analyst specializing in comprehensive information gathering, synthesis, and insight generation. Masters research methodologies, data analysis, and report creation with focus on delivering action...

GitHub

resonance-researcher

manusco

Research Engineer Specialist. Use this for deep technical investigations, comparing options, and synthesizing complex information.

GitHub

symmetry-discovery-questionnaire

lyndonkl

Use when ML engineers need to identify symmetries in their data but don't know where to start. Invoke when user mentions data symmetry, invariance discovery, what transformations matter, or needs help recognizi...

GitHub

causal-scientist

omer-metin

Causal inference specialist for causal discovery, counterfactual reasoning, and effect estimationUse when "causal inference, causal discovery, counterfactual, intervention effect, confounder, structural causal...

GitHub

synthetic-data

omer-metin

Patterns for generating synthetic data for ML training, testing, and privacy. Covers LLM-based generation, tabular synthesis, and quality validation. Use when "synthetic data, generate training data, fake data...

GitHub

monte-carlo

omer-metin

Design and implement Monte Carlo methods for uncertainty quantification, risk analysis, and probabilistic simulations across scientific and financial domains. Use when "monte carlo, random sampling, uncertainty...

GitHub

agent-based-modeling

omer-metin

Design and implement agent-based models (ABM) for simulating complex systems with emergent behavior from individual agent interactions. Use when "agent-based, multi-agent, emergent behavior, swarm simulation, s...

GitHub

scientific-method

omer-metin

The scientific method applied to computational research, data science, and experimental software engineering. Covers hypothesis formulation, experimental design, controls, reproducibility, and avoiding common m...

GitHub

protein-structure

omer-metin

Patterns for protein structure prediction using AlphaFold2/ColabFold, structural analysis, model quality assessment, and integration with experimental data. Covers best practices and critical interpretation of...

GitHub

physics-simulation

omer-metin

Patterns for physics-based simulation including numerical integration, rigid body dynamics, fluid simulation, finite element methods, and multi-physics coupling. Covers accuracy, stability, and performance. Use...

GitHub

deep-research

liangdabiao

Conduct deep research on any topic using parallel subagents and web tools (web_search, web_fetch, playwright). Use for queries that require comprehensive research from multiple perspectives.

GitHub

research-subagent

liangdabiao

Internal skill - Research subagent that executes focused research tasks using web tools. Called automatically by the deep-research lead agent.

GitHub

research-ai-tools

omer-metin

Master the AI tools that accelerate research and information gathering. From market research to academic analysis, find insights faster and make better decisions. Use when "research, find information, academic...

GitHub

synthesize

TaylorHuston

Synthesize information across multiple sources into a structured document. Processes sources in batches across sessions to handle more data than fits in context. Discovers and queues related sources automatical...

Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.

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