メニュー
このリポジトリの skills
SkillsMP は MarieLynneBlock/arcanum-artifex から 305 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
MarieLynneBlock/arcanum-artifex収集済み skill 305 件中 40 件を表示しています。
Process-based discrete-event simulation framework in Python. Use this skill when building simulations of systems with processes, queues, resources, and time-based events such as manufacturing systems, service operations, network traffic, logistics, or any…
原文の言語: 英語
Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations. Best for single-agent RL with Gymnasium…
原文の言語: 英語
Guided statistical analysis with test selection and reporting. Use when you need help choosing appropriate tests for your data, assumption checking, power analysis, and APA-formatted results. Best for academic research reporting, test selection guidance. For…
原文の言語: 英語
Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and inference. Best for econometrics, time series, rigorous inference with coefficient tables. For guided…
原文の言語: 英語
Query STRING API for protein-protein interactions (59M proteins, 20B interactions). Network analysis, GO/KEGG enrichment, interaction discovery, 5000+ species, for systems biology.
原文の言語: 英語
Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic…
原文の言語: 英語
Efficient storage and retrieval of genomic variant data using TileDB. Scalable VCF/BCF ingestion, incremental sample addition, compressed storage, parallel queries, and export capabilities for population genomics.
原文の言語: 英語
Zero-shot time series forecasting with Google's TimesFM foundation model. Use for any univariate time series (sales, sensors, energy, vitals, weather) without training a custom model. Supports CSV/DataFrame/array inputs with point forecasts and prediction…
原文の言語: 英語
Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.
原文の言語: 英語
PyTorch-native graph neural networks for molecules and proteins. Use when building custom GNN architectures for drug discovery, protein modelling, or knowledge graph reasoning. Best for custom model development, protein property prediction, retrosynthesis.…
原文の言語: 英語
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarisation, image…
原文の言語: 英語
Generate concise (3-4 page), focused medical treatment plans in LaTeX/PDF format for all clinical specialties. Supports general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management.…
原文の言語: 英語
Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use this for direct HTTP/REST work or UniProt-specific…
原文の言語: 英語
Query the U.S. Treasury Fiscal Data API for federal financial data including national debt, government spending, revenue, interest rates, exchange rates, and savings bonds. Access 54 datasets and 182 data tables with no API key required. Use when working with…
原文の言語: 英語
Access USPTO APIs for patent/trademark searches, examination history (PEDS), assignments, citations, office actions, TSDR, for IP analysis and prior art searches.
原文の言語: 英語
Use this skill for processing and analysing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualisation of big data, and machine learning on…
原文の言語: 英語
Access comprehensive LaTeX templates, formatting requirements, and submission guidelines for major scientific publication venues (Nature, Science, PLOS, IEEE, ACM), academic conferences (NeurIPS, ICML, CVPR, CHI), research posters, and grant proposals (NSF,…
原文の言語: 英語
Run structured What-If scenario analysis with multi-branch possibility exploration. Use this skill when the user asks speculative questions like "what if...", "what would happen if...", "what are the possibilities", "explore scenarios", "scenario analysis",…
原文の言語: 英語
Use this skill to create high-quality academic papers, literature reviews, grant proposals, clinical reports, and other research and scientific documents backed by comprehensive research and real, verifiable citations. Use this skill whenever the user asks…
原文の言語: 英語
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting,…
原文の言語: 英語
Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.
原文の言語: 英語
Access ZINC (230M+ purchasable compounds). Search by ZINC ID/SMILES, similarity searches, 3D-ready structures for docking, analog discovery, for virtual screening and drug discovery.
原文の言語: 英語
Pre-breach impact analysis: inventories sensitive data (PII, PHI, PCI-DSS, credentials), traces data flows, scores exposure vectors, and produces a regulatory blast radius report with fine ranges sourced verbatim from GDPR Art. 83, CCPA § 1798.155(a), and…
原文の言語: 英語
Apply GDPR-compliant engineering practices across your codebase. Use this skill whenever you are designing APIs, writing data models, building authentication flows, implementing logging, handling user data, writing retention/deletion jobs, designing cloud…
原文の言語: 英語
AI-powered codebase security scanner that reasons about code like a security researcher — tracing data flows, understanding component interactions, and catching vulnerabilities that pattern-matching tools miss. Use this skill when asked to scan code for…
原文の言語: 英語
Full STRIDE-A threat model analysis and incremental update skill for repositories and systems. Supports two modes: (1) Single analysis — full STRIDE-A threat model of a repository, producing architecture overviews, DFD diagrams, STRIDE-A analysis, prioritised…
原文の言語: 英語
Deconstruct code into bite-sized, logical chunks from a coaching perspective. Remove abstraction, explain the "why" behind each concept, identify best practices, code smells, and cognitive load issues. Use structured frameworks to provide thorough,…
原文の言語: 英語
For each syllabus topic, extract from the provided material: - What it is (1 line definition — exam-ready) - 3–5 key points an examiner expects - Important keywords to use in the answer (bold them) - Any important diagram or figure — describe what it shows in…
原文の言語: 英語
Produce Philippe Kruchten's 4+1 architectural view model for a software system. This is the core method skill: audience routing, concerns, per-view generation, and cross-view consistency. It outputs canonical diagram-as-code (Mermaid / PlantUML) plus view…
原文の言語: 英語
Use when creating, editing, or generating draw.io diagram files (.drawio, .drawio.svg, .drawio.png). Covers mxGraph XML authoring, shape libraries, style strings, flowcharts, system architecture, sequence diagrams, ER diagrams, UML class diagrams, network…
原文の言語: 英語
Generate Miro board prompts for architecture diagrams. Use this skill to produce per-view Miro prompts from canonical 4+1 diagram sources, with RISEN structure, strict scope boundaries, and track-specific validation.
原文の言語: 英語
Query JASPAR for transcription factor binding site (TFBS) profiles (PWMs/PFMs). Search by TF name, species, or class; scan DNA sequences for TF binding sites; compare matrices; essential for regulatory genomics, motif analysis, and GWAS regulatory variant…
原文の言語: 英語
Interface for MCP (Model Context Protocol) servers via CLI. Use when you need to interact with external tools, APIs, or data sources through MCP servers, list available MCP servers/tools, or call MCP tools from command line.
原文の言語: 英語
Produces a traceable acceptance test plan with individually numbered test cases. Each test case maps to a source requirement (user story, use case, or FR), specifies preconditions, steps, and expected results, and includes coverage of the happy path, edge…
原文の言語: 英語
Provides a repeatable, evidence-based framework for reviewing software architectures.
原文の言語: 英語
Provides a repeatable framework for identifying and prioritising gaps between where things are now and where they need to be.
原文の言語: 英語
Generates Miro board content in two modes:
原文の言語: 英語
Produces a structured process map with swim lanes, task nodes, decision diamonds, and handoff arrows. Output is in **Mermaid** flowchart notation (renderable in GitHub, VS Code, Confluence, and Miro) or **BPMN-lite** text when a formal notation is required.
原文の言語: 英語
Prompt for creating an Epic Product Requirements Document (PRD) for a new epic. This PRD will be used as input for generating a technical architecture specification.
原文の言語: 英語
Generates a Business Requirements Document (BRD) or Functional Requirements Specification (FRS) skeleton populated from the user's input. It structures requirements with unique IDs, priority, source, and acceptance notes — making them traceable and reviewable.
原文の言語: 英語