データ・AIのスキル

Nuxt patterns - file-based routing, data fetching (useFetch/useAsyncData), useState, server routes, middleware, auto-imports, layouts, SEO

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。

Socket.IO v4.x client patterns, connection lifecycle, reconnection, authentication, rooms, namespaces, acknowledgments, binary data, TypeScript integration

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。

tRPC type-safe API patterns — routers and procedures, input validation, context and middleware, TRPCError, and the typed client bridge

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。

Specification frameworks for features that call a model — approach tier, model pinning, output contracts, budgets, failure modes and eval design. Load when a spec touches model calls, prompts, retrieval, tool calling, agent loops or evals.

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 integration review patterns. Use when reviewing model API calls, prompt construction, LLM output handling, RAG pipelines, and tool-calling code. Covers prompt-injection call-chain tracing, output validation, stop reasons, token budgets, retry and timeout handling, streaming, and key/PII exposure.

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。

Beautiful interactive CLI prompts with @clack/prompts and custom prompts with @clack/core

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。

Direct PostgreSQL access with node-postgres (pg) -- connection pools, parameterized queries, transactions, streaming, LISTEN/NOTIFY, error 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。

LlamaIndex.TS data framework for RAG, indexing, retrieval, query engines, chat engines, and agentic workflows in TypeScript

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。

Speech-to-text transcription and translation via OpenAI Audio API -- models, response formats, timestamps, prompting, streaming, chunking, and diarization

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。

PostHog event tracking, user identification, group analytics for B2B, GDPR consent patterns. Use when implementing product analytics, tracking user behavior, setting up funnels, or configuring privacy-compliant tracking.

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。

Direct MySQL database access with mysql2 driver -- connection pools, prepared statements, transactions, streaming, typed queries, error 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。

LangChain.js patterns for building LLM applications — chat models, LCEL chains, prompt templates, structured output, agents, tools, RAG, streaming, and LangSmith tracing

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。

Provider-agnostic patterns for LLM function calling, tool loops, and agentic workflows

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。

PostHog analytics and feature flags setup

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。

Entry point and router for every Expo or EAS task. Load this skill first — before writing code and before choosing another expo-* / eas-* skill — when the request, PRD, or spec mentions Expo, EAS, Expo Go, or an expo-* package, or the project has an `expo` dependency in `package.json`. Within that gate it also covers app specs and designs to implement (tabs, stacks, maps, lists, navigation, building from a screenshot), and phrasings like 'implement a mobile app', 'make my app look native', 'add navigation', 'fetch some data', 'upgrade my SDK', 'add Expo to my existing native app', 'ship to the App Store', or 'I'm new to Expo, where do I start'. A fully specified request (SDK pinned, libraries named, layout given) still routes through here — the shared setup rules still apply. Do NOT load it when neither signal is present: a bare React Native project with no `expo` dependency is not Expo work. Detects the real goal, routes to the right expo-* / eas-* skill, and owns the shared setup 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。

Use when implementing or debugging ANY network request, API call, or data fetching. Covers fetch API, React Query, SWR, error handling, caching, offline support, loading/empty/error screen states, and Expo Router data loaders (`useLoaderData`).

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。

Integrate Expo and React Native into an existing native iOS or Android app. Use for brownfield, embedding a React Native screen in SwiftUI/UIKit or Kotlin, or AAR/XCFramework packaging. Covers isolated and integrated approaches. For building or distributing a purely native app with EAS, use eas-app-stores.

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。

Produce the monthly "Stablecoin Pulse" 2-page PDF for a partner team (default Polaris) from Pharos API data plus X and web research, explaining why supply, chains, and pegs moved. Use at month end or when asked for a monthly stablecoin trends/pulse report; not for the daily digest or Telegram pulse.

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。

Draft a short, prioritized questionnaire for a collaborating stablecoin team when public evidence cannot resolve important Pharos data or confidence gaps.

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。

Prove that a proposed active stablecoin can enter Pharos runtime data with both a fetchable price and a fetchable market-cap/circulating-supply path. Use before active additions and pre-launch promotions.

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 Prisma Next queries for Postgres, SQLite, or Mongo — pick a lane (Postgres/SQLite `db.orm.<Model>` + `db.sql.<table>`; Mongo `db.orm.<root>` + `db.query.from(...)` pipeline builder), filter / project / sort / paginate, eager-load with `.include(...)`, Postgres/SQLite `db.transaction(...)`, Postgres/SQLite ORM `.aggregate(...)`, Mongo aggregations via query builder, namespace-aware accessors (`db.orm.<ns>.<Model>`, `db.sql.<ns>.<table>`). Triggers: query, where, match, select, project, orderBy, take, skip, include, lookup, first, all, count, aggregate, group, create, update, delete, upsert, returning, transaction, db.close, script teardown, variant, polymorphism, drizzle-style, kysely-style. Notes: `.all()` is a Thenable (just `await` it), iterators are single-use (`RUNTIME.ITERATOR_CONSUMED`), Postgres `count` is `number` while sum/avg/min/max are `number | null`, ranges use chained `.where()` or `and(...)` (no `.between(...)`).

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 full feature in this Flutter repository that includes backend or storage data flow: read API schema, create DTOs, map DTOs to entities, add Riverpod use cases, connect feature state, and render UI data. Use when a task goes beyond a screen and needs real data integration.

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 preparing a desktop or web app update for commit, packaging, installer validation, GitHub publication, release asset upload, or old-release pruning. Protects user data and verifies that published artifacts match the tested build.

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 generative UI with OpenUI — any LLM provider, any backend language. Scaffold, integrate, validate.

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。