'js' 검색 결과

Build Next.js 14+ applications with App Router, server-rendered components, and form actions. Produces routes, page layouts, data fetching, loading and error states, and SEO metadata, while supporting performance optimization and deployment preparation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building pages and layouts with App Router
• Implementing form submissions with Server Actions
• Adding loading states, error handling, and SEO metadata

Continue analysis after repeated tool failures by embedding known data in Python scripts run through run_shell. Save intermediate results as JSON with timestamps and source metadata, creating records that can be checked and reused in later steps.

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• Continuing analysis when search and execution tools fail
• Comparing prices using competitor data already available
• Saving intermediate results for later review

Integrate charts and architecture diagrams into React or Next.js apps. Plan which parts run in the browser, separate rendering from application state, and address loading performance, mobile layouts, accessibility, and shareable views.

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• Integrating D3 charts into React components
• Choosing browser or server rendering in Next.js
• Sharing chart filters and selections through URLs

Write, review, and refactor React and Next.js code using performance guidelines from Vercel Engineering. Prioritize improvements to data fetching, downloaded code size, server processing, and unnecessary rendering, with rule files providing explanations and code examples.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing React code for performance issues
• Reducing delays in Next.js data fetching
• Reducing downloaded code size and load times

Write, review, and refactor React and Next.js code using Vercel's performance guidelines. Apply prioritized rules to reduce sequential data fetching, shrink downloaded code, improve server processing, and avoid unnecessary updates to the interface.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing React and Next.js code for performance issues
• Improving data fetching that waits on sequential requests
• Reducing downloaded JavaScript and page load times

TJS2 (吉里吉里Z 内蔵スクリプト言語) の言語仕様と組み込みクラスのリファレンス。.tjs ファイル / *.ks (KAG) 内の埋め込みスクリプト / TJS2 コード断片 を扱う、書く、レビューする、デバッグするときに使う。JavaScript / TypeScript に似ているが文法と意味論が違うので、JS の感覚で書くと壊れる場合が多い。組み込みクラス (Array / Dictionary / Date / Math / RegExp / Exception) の API もここに集約。**呼び出されたら必ず「JS との主な違い」セクションを最初に確認し、その上で必要な詳細リファレンスを Read で取りに行くこと。** 吉里吉里Z 本体のクラス API (Window / Layer / System / Storages / Bitmap 等) や engine 内部はこのスキルの対象外。

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

음성 파일을 OpenAI 전사 API로 보내 결과를 텍스트나 JSON으로 저장합니다. 모델과 언어를 지정하고 화자별로 발언을 구분할 수 있습니다.

• 회의 녹음을 텍스트로 변환합니다
• 인터뷰에서 화자를 구분합니다
• 전사 결과를 JSON으로 저장합니다

Java의 tinystruct로 터미널과 웹에서 함께 호출할 기능을 구현합니다. 시작 스크립트 생성부터 API, 데이터 저장, 테스트까지 개발 절차를 안내합니다.

• 터미널과 웹에서 사용할 기능 구현
• 누락된 시작 스크립트 생성
• JSON API와 데이터 저장 구현

React와 Next.js의 로딩과 조작 반응 속도를 점검하는 지침입니다. 데이터 요청 대기, 초기 JavaScript 용량, 반복 렌더링 등을 우선순위에 따라 살펴봅니다.

• 페이지 로딩 지연 조사
• 브라우저에 전달하는 JavaScript 용량 점검
• 반복 렌더링과 조작 지연 줄이기

Debug Node.js from the terminal by pausing execution, inspecting variables, and tracing function calls. Use interactive commands or scripts to investigate failing tests, collect runtime state, and capture CPU profiles or memory snapshots.

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• Inspecting intermediate state in failing Node.js tests
• Tracing function calls and unexpected variable values
• Investigating stalled asynchronous processing

Export recorded AI usage costs and budgets as Prometheus metrics or JSON. Feed external dashboards with totals, model tier breakdowns, session costs, and budget utilization, or send the same data to a webhook endpoint.

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• Refreshing cost metrics for Grafana or Prometheus
• Sending a one-time cost report to a webhook
• Providing budget utilization data for monitoring

Audit HTML page size and identify oversized embedded JSON, SVGs, images, or scripts. Use the findings to plan lighter pages and investigate whether document size could explain content missing from Google's search index.

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• Investigating content missing from Google's index
• Reviewing large JSON payloads embedded in HTML
• Checking HTML size across an e-commerce site

Turn work history, education, and skills into a complete resume for Reactive Resume. Gather missing facts through conversation and produce JSON, a structured data format, with the chosen template and layout.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Create a new resume through conversation
• Convert work history into Reactive Resume JSON
• Choose a resume template and section order

Use Outlines to make language models produce data in a defined format. The skill covers extracting information into JSON, restricting classification labels, and applying Pydantic models, which define fields and data types, with local model backends.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Extracting company or profile details into JSON
• Classifying text using a fixed set of labels
• Generating text that matches a specified pattern

Creates test starters for React and Next.js applications and analyzes coverage reports to find untested code. Supports unit, integration, and browser-based tests, simulated API responses, reusable test data, and test runner configuration.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Generating test starters for React components
• Finding untested code before a release
• Creating browser tests from Next.js routes

Helps integrate YAML output into json-render, turning incoming text into incremental UI updates. Covers prompt generation, streaming parsing, and targeted edits to existing UI specifications through merge, patch, or diff formats.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Render UI updates as YAML arrives
• Generate prompts for YAML output
• Apply partial edits to existing UI specifications

Use Outlines to make language models produce data in a defined format. The skill covers extracting information into JSON, restricting classification labels, and applying Pydantic models, which define fields and data types, with local model backends.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Extracting company or profile details into JSON
• Classifying text using a fixed set of labels
• Generating text that matches a specified pattern

Build LLM serving workflows that produce JSON or other required formats. The skill covers reusing computation for shared prompts, tool calls, and ongoing conversations, with examples for server setup and structured output.

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• Extracting article details into JSON
• Building agents that call tools
• Reusing shared prompts across conversations

Add URL handlers to a TypeScript server built with Node's native HTTP module. The skill follows an existing switch/case router, connects named asynchronous handlers, and covers JSON responses, error handling, and optional shared request body parsing.

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• Adding an API endpoint to a native Node HTTP server
• Connecting a route file to an existing switch/case router
• Sharing JSON request body parsing across routes

Prepare a ChatGPT Apps submission JSON file by inspecting an MCP server, which exposes tools to AI agents. Generate app details, tool behavior justifications, and test cases, then report review findings and missing output schemas.

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• Generate a JSON file for a ChatGPT Apps submission
• Check tool annotations against implementation
• Prepare positive and negative review test cases

Retrieve gene data, search downloads, and tissue or cell-line pages from Human Protein Atlas. Get concise summaries by default, with raw JSON or HTML saved to a file only when requested.

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• Look up gene data by Ensembl ID
• Review Human Protein Atlas search results
• Check tissue and cell-line pages

Retrieve GTEx associations between a genetic variant and gene expression in individual tissues. Supply one rsID or genome coordinate, and receive JSON with the resolved variant, association rows, counts, and warnings.

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• Retrieve tissue-specific eQTL associations for an rsID
• Query GTEx using GRCh37 coordinates
• Limit association rows returned as JSON

Create interactive views of dense datasets, spatial paths, and flows using WebGL, which uses the GPU for rendering. Choose suitable libraries and design navigation, labels, animation, and static alternatives around the analytical task.

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• Explore spatial trajectories and point clouds
• Build dense scatterplots and network views
• Animate flows between locations or nodes

Apply Vercel Engineering’s performance guidelines when writing, reviewing, or refactoring React and Next.js code. Prioritize improvements to data fetching, downloaded code size, server processing, and unnecessary rendering using rules with explanations and code examples.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review React components for performance issues
• Improve data fetching in Next.js pages
• Reduce downloaded code and loading time