300 件（bg-szy のリポジトリ） ・ 人気順
概要と使いどころ
Search and retrieve preprints from arXiv via the Atom API. Use this skill when searching for papers in physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering, or economics by keywords, authors, arXiv IDs, date ranges, or categories.
日本語の概要は準備中です。原文の説明を表示しています。
Search arXiv physics, math, and computer science preprints using natural language queries. Powered by Valyu semantic search.
日本語の概要は準備中です。原文の説明を表示しています。
Time-blind friendly planning, executive function support, and daily structure for ADHD brains. Specializes in realistic time estimation, dopamine-aware task design, and building systems that actually work for neurodivergent minds.
日本語の概要は準備中です。原文の説明を表示しています。
Master Python asyncio, concurrent programming, and async/await patterns for high-performance applications. Use when building async APIs, concurrent systems, or I/O-bound applications requiring non-blocking operations.
日本語の概要は準備中です。原文の説明を表示しています。
This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
日本語の概要は準備中です。原文の説明を表示しています。
Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.
日本語の概要は準備中です。原文の説明を表示しています。
Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing.
日本語の概要は準備中です。原文の説明を表示しています。
API + Python SDK for ordering cell-free protein expression and binding assays. Submit sequences for expression (10–100 µg), measure binding affinity (KD) against targets, track status, and retrieve results programmatically — no wet-lab setup. Built for ML-guided directed evolution and antibody/nanobody optimization. Requires Adaptyv account and API key.
日本語の概要は準備中です。原文の説明を表示しています。
Engineering operating model for teams where AI agents generate a large share of implementation output.
日本語の概要は準備中です。原文の説明を表示しています。
scikit-learn compatible Python toolkit for time series ML: classify, cluster, regress, segment, transform with 30+ algorithms (ROCKET, InceptionTime, KNN-DTW, HIVE-COTE, WEASEL). Handles panel, multivariate, and unequal-length series. Maintained successor to sktime. Alternatives: sktime (larger ecosystem), tslearn (fewer algorithms), catch22 (features only).
日本語の概要は準備中です。原文の説明を表示しています。
Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code.
日本語の概要は準備中です。原文の説明を表示しています。
Use the AgentD workflow to mine evidence, design molecules, and rank candidates with SAR plus ADMET annotations for early drug discovery tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Eliminates AI-generated writing patterns that erode reader trust. Use when writing or editing articles, docs, or press releases.
日本語の概要は準備中です。原文の説明を表示しています。
Use after generating code, after accepting AI suggestions, or when reviewing AI-written modules. Also use when code works but feels brittle, when error handling seems thin, when orphaned resources or missing cleanup are suspected, or when the agent claims done but hidden debt may exist. Catches the specific failure patterns AI agents produce that humans would not.
日本語の概要は準備中です。原文の説明を表示しています。
Validate protein designs using AlphaFold2 structure prediction. Use this skill when: (1) Validating designed sequences fold correctly, (2) Predicting binder-target complex structures, (3) Calculating confidence metrics (pLDDT, pTM, ipTM), (4) Self-consistency validation of designs, (5) Multi-chain complex prediction with AlphaFold-Multimer.
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Access real-time and historical stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, and 50+ technical indicators via the Alpha Vantage API. Use when fetching stock prices (OHLCV), company fundamentals (income statement, balance sheet, cash flow), earnings, options data, market news/sentiment, insider transactions, GDP, CPI, treasury yields, gold/silver/oil prices, Bitcoin/crypto prices, forex exchange rates, or calculating technical indicators (SMA, EMA, MACD, RSI, Bollinger Bands). Requires a free API key from alphavantage.co.
日本語の概要は準備中です。原文の説明を表示しています。
An advanced agent for de novo antibody design and optimization using state-of-the-art protein language models (MAGE, RFdiffusion).
日本語の概要は準備中です。原文の説明を表示しています。
Access AlphaFold's 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.
日本語の概要は準備中です。原文の説明を表示しています。
API hardening for Express, FastAPI, and serverless. Use for rate limiting, CORS, input validation, API keys, or OWASP API Top 10.
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Migrate from AngularJS to Angular using hybrid mode, incremental component rewriting, and dependency injection updates. Use when upgrading AngularJS applications, planning framework migrations, or modernizing legacy Angular code.
日本語の概要は準備中です。原文の説明を表示しています。
AI-powered design of armored CAR-T cells with cytokine/chemokine expression for enhanced solid tumor efficacy, including IL-12, IL-15, IL-18, and IL-7 armoring strategies.
日本語の概要は準備中です。原文の説明を表示しています。
Understand anti-reversing, obfuscation, and protection techniques encountered during software analysis. Use this skill when analyzing malware evasion techniques, when implementing anti-debugging protections for CTF challenges, when reverse engineering packed binaries, or when building security research tools that need to detect virtualized environments.
日本語の概要は準備中です。原文の説明を表示しています。
Write articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credibility matter.
日本語の概要は準備中です。原文の説明を表示しています。
Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns.
日本語の概要は準備中です。原文の説明を表示しています。