2,374 件 ・ 関連度順
概要と使いどころ
Execute via @babysitter. Use this skill when asked to babysit a task, do anything that is structured process-driven (even a loop) or whenever it is called explicitly. (babysit, babysitter, with a process, orchestrate, orchestrate a run, workflow, loop until, etc.)
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。
Retrieve mouse phenotype data from the Jackson Laboratory Mouse Phenome Database (MPD) via its REST API. Browse 520+ projects, look up per-project measure metadata, pull strain-level means (raw or LS-mean adjusted) and per-animal values, find measures by MP/VT ontology terms, and resolve strain nomenclature or gene coordinates. Use for QTL support, cross-strain comparison, mouse model selection, and ontology-driven phenotype discovery. Use monarch-database for disease-gene-phenotype knowledge graphs; ensembl-database for mouse genome annotations.
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。
Designing scientific schematics, diagrams, and graphical abstracts. Covers tool selection (BioRender, Inkscape, Affinity, PowerPoint), design principles for pathway diagrams, mechanism schematics, experimental workflows, and journal graphical abstracts. Includes composition, icon sourcing, color for biological entities, and accessibility. Use when creating illustrative (not data-driven) scientific figures.
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Domain-Driven Design architecture for claude-flow v3. Implements modular, bounded context architecture with clean separation of concerns and microkernel pattern.
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Canonical rules for writing tests in the Shift codebase. Use whenever you add, rewrite, or review a `.test.ts` or `.spec.ts` file — or any time you're about to mock, stub, or spy your way around a testing problem. Covers TestEditor-based tests and desktop E2E tests driven through EditorDriver.
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。
Provides implementation patterns for Clean Architecture, Domain-Driven Design (DDD), and Hexagonal Architecture (Ports & Adapters) in NestJS/TypeScript applications. Use when structuring complex backend systems, designing domain layers with entities/value objects/aggregates, implementing ports and adapters, creating use cases, or refactoring from anemic models to rich domain models with dependency inversion.
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Provides implementation patterns for Clean Architecture, Hexagonal Architecture (Ports & Adapters), and Domain-Driven Design in Python applications with FastAPI or Flask. Use when designing maintainable backends with separation of concerns, implementing repository patterns, creating entities/value objects/aggregates, or structuring domain logic independent of frameworks for testability.
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。
Provides implementation patterns for Clean Architecture, Hexagonal Architecture (Ports & Adapters), and Domain-Driven Design in Java 21+ Spring Boot 3.5+ applications. Use when structuring layered architectures, separating domain logic from frameworks, implementing ports and adapters, creating entities/value objects/aggregates, or refactoring monolithic codebases for testability and maintainability.
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。
Provides and generates LangChain4j tool and function calling patterns: annotates methods as tools with @Tool, configures tool executors, registers tools with AiServices, validates tool parameters, and handles tool execution errors. Use when building AI agents that call tools, define function specifications, manage tool responses, or integrate external APIs with LLM-driven applications.
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 when executing a pre-registered analysis plan with mostly independent steps in the current session
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。
Compress construction schedules using crashing and fast-tracking techniques. Analyze cost-time tradeoffs and find optimal acceleration 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。
Generate safety toolbox talks for construction crews. Create contextual safety briefings based on weather, work activities, and recent incidents. Support multiple languages.
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。
Create n8n workflow for daily task assignment from PTO engineer to foreman via Telegram bot with status reporting.
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。
Process construction payment applications. Validate schedule of values, calculate retainage, track billing status, and generate G702/G703 forms.
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。
Assess company readiness for construction industry uberization. Analyze data transparency, process automation, and competitive positioning against open data platforms.
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 construction schedule delays for claims and recovery. Perform time impact analysis, identify delay causes, calculate damages, and document for disputes.
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。
Forecast construction project cash flow. Project income and expenses, identify funding gaps, and optimize payment timing for improved financial management.
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。
Track construction retainage/retention amounts. Monitor held amounts by subcontractor, track release conditions, and manage retainage billing.
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。
Curated few-shot examples for construction AI tasks: classification, extraction, analysis. Domain-specific examples for improved LLM performance.
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。
Automate daily construction report generation using n8n workflow 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。
Reusable prompt templates for construction AI tasks: cost estimation, schedule analysis, document processing, BIM queries. Structured prompts for consistent results.
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。
Automatically extract patterns, best practices, and reusable knowledge from construction automation sessions to improve future performance.
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 construction data inputs before processing: cost estimates, schedules, BIM data, field reports. Catch errors early with domain-specific rules.
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。
Security review checklist for construction software systems. Use when building integrations, APIs, data pipelines, or dashboards for construction projects.
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。