4,184 件 ・ 関連度順
概要と使いどころ
Audits and rewrites landing pages, homepages, and sales pages to increase conversion — diagnosing why a page is not converting, rewriting headlines, hero copy and calls to action, and prioritizing which changes to test first. Use this when a page underperforms, when someone pastes a URL or screenshot asking what is wrong, when writing a new page, or when deciding which conversion changes are worth testing.
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。
Guide for creating and editing Obsidian notes using Obsidian Flavored Markdown (OFM). Covers wikilinks, embeds, callouts, YAML properties, and knowledge organization best practices.
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。
Switch Agent persona preset. Supports 8 presets including default assistant, business, tech expert, butler, girlfriend, boyfriend, family, and Jarvis. Use when user asks to change communication style or personality.
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。
Manage Obsidian vaults with full support for Obsidian Flavored Markdown — wikilinks, embeds, callouts, YAML properties, Dataview queries, Canvas, and Bases. Organize notes using MOCs (Maps of Content), atomic note principles, and consistent folder/tag taxonomies. Always ask the user where to save before creating notes.
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。
Designs complete single-cell research plans from a user-provided biomedical direction. Always use this skill whenever a user wants to design, scope, or structure a single-cell study — including disease-focused, mechanism-focused, biomarker-focused, translational, perturbation-inspired, or validation-aware projects. It should define the research question, choose the best-fit study pattern, recommend sample grouping logic, suggest reference datasets as examples only, specify the core analysis modules, propose a validation ladder, and output four workload configurations (Lite / Standard / Advanced / Publication+). Never fabricate datasets, sample metadata, accession numbers, cohort availability, cell-type labels, external validation resources, or literature references. Always include the mandatory Dataset Disclaimer immediately before any workflow section that mentions datasets or public resources.
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。
Designs cell-based and animal-based validation plans that translate computational, omics, biomarker, genetic, or clinical findings into experimentally testable validation routes. Always use this skill whenever a user wants to move from an in silico, statistical, or clinical association finding toward wet-lab validation using cell systems, organoid-like systems, xenograft or genetically relevant animal models. It should define the exact claim to test, separate mechanism-testing from association-support and translational-support goals, choose the best-fit model family, specify perturbation strategy, readouts, controls, sequencing of experiments, and four workload configurations (Lite / Standard / Advanced / Publication+) with one recommended primary plan. Never fabricate model availability, reagent availability, species relevance, assay feasibility, phenotype penetrance, expected effect sizes, validation success, or literature references.
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。
Guides Stripe integration decisions across development and test environment planning (separate sandboxes vs the shared test mode sandbox), API selection (Checkout Sessions vs PaymentIntents), Connect platform setup (Accounts v2, controller properties), billing/subscriptions, tax and registrations (Stripe Tax, automatic_tax, product tax codes), Treasury financial accounts, integration options (Checkout, Payment Element), migrating from deprecated Stripe APIs, and security best practices (API key management, API key permissions, webhooks, OAuth). Use when planning, building, modifying, testing, or reviewing any Stripe integration, including choosing a development environment, accepting payments, building marketplaces, integrating Stripe, processing payments, setting up subscriptions, collecting sales tax, VAT, or GST, creating connected accounts, or implementing secure key handling.
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。
World-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence. Includes experiment design, feature engineering, model evaluation, and stakeholder communication. Use when designing experiments, building predictive models, performing causal analysis, or driving data-driven decisions.
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。
Analyze media file properties - duration, resolution, bitrate, codecs, and stream information
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。
Guide for translating Python classes, inheritance, and object-oriented patterns to Scala. Use when converting Python code with classes, dataclasses, abstract classes, inheritance, properties, static methods, class methods, or design 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。
World-class data engineering skill for building scalable data pipelines, ETL/ELT systems, real-time streaming, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, Flink, Kinesis, and modern data stack. Includes data modeling, pipeline orchestration, data quality, streaming quality monitoring, and DataOps. Use when designing data architectures, building batch or streaming data pipelines, optimizing data workflows, or implementing data governance.
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。
World-class Java and Spring Boot development skill for enterprise applications, microservices, and cloud-native systems. Expertise in Spring Framework, Spring Boot 3.x, Spring Cloud, JPA/Hibernate, and reactive programming with WebFlux. Includes project scaffolding, dependency management, security implementation, and performance optimization.
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。
Query PubChem via PUG-REST API/PubChemPy (110M+ compounds). Search by name/CID/SMILES, retrieve properties, similarity/substructure searches, bioactivity, for cheminformatics.
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。
Analyzes 3D mesh files (STL) to calculate geometric properties (volume, components) and extract attribute data. Use this skill to process noisy 3D scan data and filter debris.
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。
Interactive PM interview with expertise-adaptive questioning for requirements elicitation
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。
Complexity-based task routing with Q-Learning optimization, Agent Booster WASM fast-path, and Mixture-of-Experts model selection.
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 modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems. Use PROACTIVELY for database optimization or complex analysis.
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。
Design service meshes with Istio or Linkerd, including traffic management, security, and observability. Use when configuring service communication, mesh policies, or multi-cluster networking.
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。
Expert startup business analyst specializing in market sizing, financial modeling, competitive analysis, and strategic planning for early-stage companies. Use PROACTIVELY when the user asks about market opportunity, TAM/SAM/SOM, financial projections, unit economics, competitive landscape, team planning, startup metrics, or business strategy for pre-seed through Series A startups.
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。
Rigorous visual validation expert specializing in UI testing, design system compliance, and accessibility verification. Masters screenshot analysis, visual regression testing, and component validation. Use PROACTIVELY to verify UI modifications have achieved their intended goals through comprehensive visual analysis.
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。
You are an expert team communication specialist focused on async-first standup practices, AI-assisted note generation from commit history, and effective remote team coordination 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。
Expert Terraform/OpenTofu specialist mastering advanced IaC automation, state management, and enterprise infrastructure patterns. Handles complex module design, multi-cloud deployments, GitOps workflows, policy as code, and CI/CD integration. Covers migration strategies, security best practices, and modern IaC ecosystems. Use PROACTIVELY for advanced IaC, state management, or infrastructure automation.
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。
Expert web researcher using advanced search techniques and synthesis. Masters search operators, result filtering, and multi-source verification. Handles competitive analysis and fact-checking. Use PROACTIVELY for deep research, information gathering, or trend analysis.
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。
Expert reverse engineer specializing in binary analysis, disassembly, decompilation, and software analysis. Masters IDA Pro, Ghidra, radare2, x64dbg, and modern RE toolchains. Handles executable analysis, library inspection, protocol extraction, and vulnerability research. Use PROACTIVELY for binary analysis, CTF challenges, security research, or understanding undocumented software.
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。