「ask」の検索結果

Diagnose data races, convert callback-based code to async/await, implement actor isolation patterns, resolve Sendable conformance issues, and guide Swift 6 migration. Use when developers mention: (1) Swift Concurrency, async/await, actors, or tasks, (2) "use Swift Concurrency" or "modern concurrency patterns", (3) migrating to Swift 6, (4) data races or thread safety issues, (5) refactoring closures to async/await, (6) @MainActor, Sendable, or actor isolation, (7) concurrent code architecture or performance optimization, (8) concurrency-related linter warnings (SwiftLint or similar; e.g. async_without_await, Sendable/actor isolation/MainActor lint).

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 and optimize React component performance issues (slow renders, re-render thrash, laggy lists, expensive computations). Use when asked to profile or improve a React component, reduce re-renders, or speed up UI updates in React apps.

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。

Scan Apple's SwiftUI documentation for deprecated APIs and update the SwiftUI Expert Skill with modern replacements. Use when asked to "update latest APIs", "refresh deprecated SwiftUI APIs", "check for new SwiftUI deprecations", "scan for API changes", or after a new iOS/Xcode release. Requires the Sosumi MCP to be available.

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。

Run a 3-leg evaluation against a newly released LLM. Leg 1 is trap questions with deterministic answers, leg 2 is an agentic orchestration task with a planted failure, leg 3 is a brownfield feature build in a real repo. Use when the user wants to vibe-check, test, evaluate, or compare a new frontier model, or mentions model-bench, model vibe check, or launch-day protocol.

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。

Applies Chesterton's Fence, Occam's Razor, the Peter Principle, and Dunning-Kruger to technical decisions. Use before refactoring, architectural changes, or any task where changing existing behavior carries risk or requires judgment about what the user actually needs.

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。

Produces thorough, multi-source cited research reports from web and news without paid APIs. Use when the user asks for deep research, landscape analysis, competitive intel, market research, or a cited report needing broad source coverage.

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。

Structured 3-phase peer review of a diff or PR — intent, issues by severity, then pointed merge-readiness questions and a verdict. Use for general code review. Not for AI workflow self-fix-and-edit (ai-systems-review) or no-edit devil's-advocate threat models (adversarial-challenge). Phase 3 asks questions only; it is not the adversarial-challenge skill.

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。

Hostile self-review of recently written AI workflow code that then applies fixes (agents, tools, chat context, summarization, tokens, attachments). Use after generating AI systems code, or when asked to self-review and harden it. Not for PR peer review (code-review) or no-edit devil's-advocate attacks (adversarial-challenge). Prefer: adversarial-challenge → decide → this skill.

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。

Generates as many digits of pi as possible and writes them into files inside a tokenMaxxing/ folder. Use when the user asks to token-maxx, fill a file with pi digits, test agent output throughput, or generate N pi files sequentially or in parallel.

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。

Writes in ASD-STE100 simplified technical English — short sentences, plain words, active voice. Use when the user wants terse technical prose, names this skill, or asks for STE100.

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。

Builds personal brand assets using Seth Godin's frameworks: signature symbol, slogan, surprise (Purple Cow), salient idea, and signature story. Use when named (branding), or when the user asks for a brand symbol, slogan, tagline, Purple Cow, counterintuitive angle, core idea, brand story, or personal brand positioning.

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 a polished frontend reference screenshot through a configurable GPT-image-2-compatible generations endpoint, save and show versioned previews inside the project, revise selected previews through a configurable /images/edits endpoint, and reproduce only the user-approved design as functional frontend code with high visual fidelity. Use when Codex is asked to design, build, restyle, or recreate a web page, application screen, dashboard, landing page, or UI component through an image-first workflow, design approval loop, screenshot-driven implementation, pixel matching, or a 1:1 frontend recreation.

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。

Review resumes, cover letters, application packages, and evidence maps from an HR perspective. Use when the user asks for 자기소개서 리뷰, 자소서 검토, HR 검토, 제출 전 점검, unsupported-claim detection, company-name residue checks, or risk-focused revision advice before applying.

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 Korean job application cover letter drafts from a question, JD, resume.md, and optional company values input. Use when the user asks for 자기소개서, 자소서, 지원동기, 입사 후 포부, 필살기, 3C4P experience decomposition, experience-based application answers, or tailored cover letter text grounded in resume.md evidence.

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 a job description, hiring post, or recruitment page for role requirements, evaluation criteria, keywords, risks, and resume or cover letter angles. Use when the user provides a JD URL/text, asks what a company is looking for, wants JD-resume gap analysis, or needs inputs for a tailored cover letter. 한국어 요청도 포함합니다 - 채용공고 분석, 공고 분석, JD 분석, 직무기술서 분석, 자격요건, 우대사항, 이 공고 뭘 원하는지, 공고랑 내 경력 비교.

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 an optional company talent, values, culture, or recruitment page and turn it into cover letter positioning guidance. Use when the user provides a company values URL/text, asks to match a cover letter to company culture, or wants talent-profile keywords connected to resume.md evidence. 한국어 요청도 포함합니다 - 인재상 분석, 기업 가치관, 회사 문화, 채용 홈페이지 분석, 기업 분석, 인재상에 맞춰서, 회사가 원하는 인재.

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。

This skill should be used when the user asks to "calculate iryubun", "遺留分侵害額", "遺留分", "遺留分侵害額請求", "遺贈", "生前贈与の遺留分算入", or wants deterministic computation of reserved-portion infringement under 民法 1042-1048.

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。

This skill should be used when the user asks to "calculate overtime", "未払残業代計算", "残業代を計算", "労基法37条", "割増賃金", "深夜労働", or wants deterministic computation of unpaid overtime wages under the Labor Standards Act Article 37.

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。

This skill should be used when the user asks to "analyze a lawsuit", "訴訟分析", "事件分析", "書面分析", "case analysis", "判決分析", "訴訟書類の整理", or wants to extract structured information from litigation documents.

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。

Provide universal memory capabilities for different AI agents and development frameworks, unifying the capture, retrieval, and management of user, project, and task context.

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 this skill whenever the user asks to inspect JoCoHunt, 조코헌트, jocohunt.jocoding.io products, ideas, rankings, makers, public security headers, or wants a CLI workflow for the Korean builder community. It runs the local `jocohunt` Go CLI, including authenticated product submission when explicitly requested.

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。

Discuss a community-edition product requirement with the user, draft a bilingual (Chinese + English) PRD for review, then — after explicit user approval — create the English-only issue on GitHub (<OWNER/REPO>). Use whenever the user wants to turn a requirement (from a Feishu doc, a meeting note, a customer ask, or a rough idea) into a GitHub issue. Triggers on phrases like "create requirement doc", "create a requirement", "put this requirement on GitHub", "create new feature issue", "draft an issue for...", or anytime the user describes a product feature/improvement they want tracked. The format is opinionated (Background / Goal / Spec / Verification / Related, NO implementation details, draft shown bilingually for human review, issue itself written in English only).

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。

This skill should be used when the user asks to "优化简历", "resume optimization", "简历诊断", "tailor resume to JD", "改简历", "resume review", "简历优化助手", or when the user mentions "校招", "社招", "ATS", "JD匹配", "Word批注", shares a .docx resume path alongside a job description, or wants to match their resume to a specific job posting. Also triggers on "resume expert", "HR feedback", "interview prep with resume".

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。

MUST USE whenever the user wants to automate a real desktop or sandbox - clicking, typing, scrolling, screenshotting, running an OS shell command, or handing a high-level 'open browser and do X' task to an autonomous computer-use agent. Wraps the trycua/cua Python toolkit via its `cua` CLI - pynput-based, cross-platform (macOS / Linux / Windows). NO custom tools are registered; you call `cua` through pi's built-in bash and read screenshots back through the Read tool. Triggers: cua, computer use, computer-use, GUI automation, screenshot the desktop, click on the screen, type into the active app, scroll the page, control my computer, drive my browser, sandbox, docker sandbox, QEMU sandbox, Lume sandbox, ComputerAgent, cua do, cua sandbox, 컴퓨터 자동화, 스크린샷 찍어, 내 컴퓨터 조작, 브라우저 열어서, 샌드박스, 화면 자동화, 마우스로 클릭, 키보드 타이핑, computer use 위임, 자동으로 클릭, 자율 에이전트로 처리.

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。