データ・AIのスキル

Use when finding and statistically confirming a reproducible Crewrift crux before changing the policy.

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。

Verify a native LLM voting advisor before trusting advisor-sensitive evaluations.

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 for Crewrift-specific data science refit recipes when optimizing a player.

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 for reusable data science refit recipes in software and coding-agent work.

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。

Opinionated house conventions for NestJS backends — module boundaries and layering, provider wiring and injection scopes, guards/interceptors/pipes/filters, DTOs and validation, domain exceptions, config, and the Nest 11 / Express 5 behaviour that compiles cleanly and fails at runtime. Use whenever the code is NestJS (`@nestjs/*` in package.json, or `@Module`/`@Injectable`/`@Controller`/`@Cron` in the file), including when the question sounds like plain TypeScript, an OOP refactor, a code review, or an ops problem — the Nest-specific answer differs from the generic one. Typical asks: scaffolding a module, adding a controller, provider, or endpoint, wiring an enhancer, a boot-time DI or circular-import failure, a response leaking entity fields despite `@Exclude()`, a cron job firing on every replica, upgrading NestJS, or reviewing a Nest diff. Not for plain Express or Fastify, Angular, frontend, SQL, or CI.

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。

Apply this opinionated workflow when reverse-engineering legacy or undocumented systems: scope, explore the code, trace data flows, document in EARS format, flag uncertainties. For code archaeology, onboarding, and requirements extraction.

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。

Task planning with scout data + task-type templates. Produces implementation checklists.

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。

shadcn-vue for Vue/Nuxt with Reka UI components and Tailwind. Use for accessible UI, Auto Form, data tables, charts, dark mode, or encountering component imports, Reka UI errors.

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Fact-forcing gate that blocks Edit/Write/Bash (including MultiEdit) and demands concrete investigation (importers, data schemas, user instruction) before allowing the action. Measurably improves output quality by +2.25 points vs ungated agents.

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 reproducible, cross-platform development environments with Flox — a declarative environment manager built on Nix. ALWAYS use this skill when the user needs to: set up a project with system-level dependencies (compilers, databases, native libraries like openssl, libvips, BLAS, LAPACK); configure reproducible toolchains for Python, Node.js, Rust, Go, C/C++, Java, Ruby, Elixir, PHP, or any language; manage environments that must work identically across macOS and Linux; pin exact package versions for a team; run local services (PostgreSQL, Redis, Kafka) alongside development tools; onboard new developers with a single command; or solve 'works on my machine' problems. Especially valuable for AI-assisted and vibe coding — Flox lets agents install tools into a project-scoped environment without sudo, system pollution, or sandbox restrictions, and the resulting environment is committed to the repo so anyone can reproduce it instantly. Use this skill even if the user doesn't mention Flox — if they describe needing reproducible, declarative, cross-platform dev environments with system packages, this is the right tool. Also use when the user mentions .flox/, manifest.toml, flox activate, or FloxHub.

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。

Apple FoundationModels framework for on-device LLM — text generation, guided generation with @Generable, tool calling, and snapshot streaming in iOS 26+.

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。

Cost optimization patterns for LLM API usage — model routing by task complexity, budget tracking, retry logic, and prompt caching.

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。

ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.

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 large data ingestion, backfill, export, ETL, warehouse loading, manifest catch-up, or table synchronization needs to become much faster while preserving data correctness.

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Build a fully automated AI-powered data collection agent for any public source — job boards, prices, news, GitHub, sports, anything. Scrapes on a schedule, enriches data with a free LLM (Gemini Flash), stores results in Notion/Sheets/Supabase, and learns from user feedback. Runs 100% free on GitHub Actions. Use when the user wants to monitor, collect, or track any public data automatically.

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。

Reverse-lookup glossary that turns a vague description of a web animation or motion effect into its exact term ("the bouncy thing when a popover opens" → Pop in; "the iOS rubber-band scroll" → Rubber-banding). Use when the user asks "what's it called when…", or describes a motion effect without knowing its name and wants the right word to prompt an AI or designer with. For naming an effect, not designing or building one.

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。

Build a motion website implementation plan (and optional starter structure) from motion prompt briefs using accessible 3D/animated UI 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。

Universal seed data generator: MIGRATE from ORM schemas or GENERATE from entity definitions to any target format

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。

Manages clusters, instances, and backups for AlloyDB for PostgreSQL, and integrates with AlloyDB model context protocol (MCP) tools for automated database 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。

Use Mermaid diagrams in DecisionsAI to explain technical topics — architecture, flows, sequences, and data models via the freestanding diagram viewer.

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。

Research and normalize MotionSites-style prompt directions, then output a clean motion prompt brief for implementation.

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。

Manages datasets, tables, and jobs in BigQuery, and integrates with BigQuery ML and Gemini for advanced data analytics and AI-driven insights. Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources, or leverage BigQuery's built-in ML capabilities. Also use when performing data analysis, ingesting data into BigQuery, or developing AI applications on BigQuery.

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 high-converting copy for any surface — landing pages, emails, ads, sales pages, product descriptions, CTAs, video scripts, and more. Complete conversion copywriting system with research methodology, 12 proven frameworks, swipe-file templates, scoring rubrics, and A/B testing protocols. Use when you need to write or review any copy meant to drive action.

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。