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概要と使いどころ
Hoyeon deep research workflow for Codex. Use when the user invokes "$hoyeon-deep-research" or wants a multi-channel cited research report using web search, browser extraction, and optional Gemini. This adapter loads the canonical deep-research skill and follows its Codex runtime surface.
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 says "/ultrawork", "ultrawork", or wants to run the full specify → execute pipeline automatically with a single command. Automated end-to-end workflow that chains specify and execute skills.
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 open-source project from What/Why perspective (not how-it's-implemented). Use when the user says "/analyze-oss", "분석해줘 이 오픈소스", "이 레포 뭐하는거야", "analyze this repo", "what does X do", "이거 왜 쓰는거야", "이 라이브러리 분석", provides a GitHub URL and wants understanding, or asks to deeply understand an OSS project's purpose, value, target users, and usage flow. Clones the repo to ~/opensource-analysis/<repo-name>/ (git pull if already exists), dispatches parallel subagents per analysis lens, then synthesizes a What/Why-focused report in chat. Supports optional user-specific follow-up questions.
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。
Plan-driven orchestrator. Reads plan.json (from /blueprint) or requirements.md, then dispatches workers to build the system. Use when: "/execute", "execute", "plan 실행", "blueprint 실행"
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", "discuss this", "think with me", "is this a good idea?", "what do you think about", "problem definition", "explore this idea", "/discuss --scored", "interview me", "clarify requirements", "요구사항 정리", "인터뷰", "딥 인터뷰", "뭘 만들어야 할지 모르겠어", Korean triggers: "같이 생각해보자", "이거 어떻게 생각해?", "문제 정의", "이게 좋은 아이디어야?", "이거 맞아?", "요구사항이 불명확", "아이디어 구체화"
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。
Recon-first browser automation. Orchestrator explores the site first via chromux, saves a guide file with insights, then delegates execution to browser-explorer agent. Use when: "/browser-work", "브라우저 작업", "사이트에서 해줘", "웹에서 해줘", "LinkedIn에서", "크롬으로", "browser task", "automate this site".
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。
Deep web research skill using parallel subagents + chromux browser-explorer + Gemini. Spawns multiple WebSearch research agents AND browser-explorer agents (via chromux for JS-heavy/dynamic sites), plus a Gemini CLI deep research source, then synthesizes everything into a cited report. Uses WebSearch, WebFetch, chromux browser-explorer, and Gemini CLI. Invoke with /deep-research <topic>.
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。
Collect diverse opinions on technical topics from developer communities. Use for "developer reactions", "community opinions" requests. Aggregates Reddit, HN, Dev.to, Lobsters, ProductHunt, 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。
This skill should be used when the user wants to verify their changes before pushing, or update the project's rule checklists. Phase 1: validate changed files against .hoyeon/rules/ checklists and report PASS/WARN. Phase 2 (conditional): propose rule additions when unmatched patterns are detected. Essential before git push. Trigger phrases: "check", "checklist", "verify changes", "what did I miss", "pre-push check", "cascading changes", "any more changes needed", "update checklist", "update rules", "rules update", "체크", "체크리스트", "변경 확인", "빠뜨린 거 없나", "push 전 확인", "뭐 더 건드려야 해?", "연쇄 변경 확인", "규칙 갱신".
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。
"/specify", "specify", "요구사항 정의", "requirements", "스펙 잡기", "뭘 만들어야 하는지", "기획 정리", "인터뷰해서 스펙" Turn a goal into structured requirements through systematic interview. Three phases: Interview → Extract → Cross-check. Writes requirements.md in the cli format (consumed by /blueprint).
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。
You are an expert in @react-three/drei, the companion library for React Three Fiber that provides 100+ ready-made components and hooks for common 3D patterns. You help developers add orbit controls, environment maps, text rendering, HTML overlays, loaders, performance utilities, shaders, and abstractions — eliminating boilerplate and letting teams focus on creative work instead of Three.js plumbing.
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 data quality in CSV, JSON, and database exports by checking for missing values, type mismatches, duplicates, outliers, and schema violations. Use when building ETL pipelines, auditing data imports, checking data freshness, or ensuring data contracts between teams. Trigger words: data quality, validation, null values, duplicates, schema check, data contract, ETL, pipeline, data drift.
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。
You are an expert in Clay, the data enrichment and outbound sales platform that pulls from 75+ data providers to build rich prospect profiles. You help teams automate lead discovery, enrich contacts with firmographic and technographic data, score leads against ICP criteria, and trigger personalized outreach sequences — replacing manual research with automated, data-driven prospecting.
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。
Guides a founder from real decisions to a short set of written company values that people can act on: collects incidents, tests each candidate value, writes it as a trade-off with behaviors and a story, and wires it into hiring, feedback and promotion. Use when someone asks to "define our company values", "write a values document", "our values are generic, fix them", "turn our values into interview questions", "what should our culture be before we hire", or wants to check whether the team lives the values it has. Produces VALUES.md, an evidence log and an interview kit.
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。
Chromatic is a visual testing service from the Storybook team that snapshots every story in a cloud browser and shows visual diffs for review on each pull request. Use when the user wants visual regression testing with Storybook, or mentions "chromatic," "visual regression," "Storybook testing," "UI review," "visual diff," or "component snapshot testing." For general screenshot comparison, see percy.
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。
You are an expert in Contentful, the API-first content platform for enterprise teams. You help developers integrate Contentful's Content Delivery API (CDN-backed, read), Content Management API (write), and Content Preview API (draft content) into websites and apps — using typed content models, localization, rich text rendering, image transformations, and webhooks for build triggers.
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 a content strategy a small team can execute: audience needs backed by counted evidence, an audit of what is already published, a topic map with one page per search intent, a scored backlog, a 90-day calendar sized to real capacity, and the numbers that will show whether it worked. Use when someone asks "what should we write about", "plan our blog", "content strategy", "content plan for next quarter", "topic clusters", "content audit", "our blog traffic is falling", or wants a pile of content ideas turned into a prioritised plan.
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 HTTP APIs and web services in Rust with Axum, the Tokio team's web framework on top of Tokio, Hyper and Tower. Use when a user asks to create a Rust REST API, add routes, extractors, JSON handlers, shared state, middleware, error handling, WebSockets, graceful shutdown or tests with Axum, or to migrate older Axum code (0.6/0.7 path syntax) to 0.8.
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。
Coordinate multiple AI agents working together on complex tasks — routing, handoffs, consensus, memory sharing, and quality gates. Use when tasks involve building multi-agent systems, coordinating specialist agents in a pipeline, implementing agent-to-agent communication, designing swarm architectures, setting up agent orchestration frameworks, or building autonomous agent teams with supervision and quality control. Covers hierarchical, mesh, and pipeline topologies.
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 and trace AI agents in Python with AgentScope, an open-source agent framework with a ReAct loop, tools, middleware, team pipelines and OpenTelemetry tracing. Use when building production agents that need observability, debugging an agent's model and tool calls, capping token spend per reply, or coordinating a leader with specialist 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。
Core marketing principles for startups. Covers positioning, messaging, channels, and growth. Focus on what works for resource-constrained teams. Battle scars included: I've watched startups burn $1M on Instagram ads because "that's where competitors are", seen "growth hacks" destroy brand trust overnight, and advised founders who scaled marketing before finding product-market fit. Contrarian take: Most startup marketing advice is backwards. The best marketing doesn't feel like marketing. Distribution comes before product features. And your first 100 customers should never come from paid ads. Use when "marketing strategy, positioning, messaging, customer acquisition, growth channels, brand, go-to-market, " mentioned.
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。
Go is the language of infrastructure. From Docker to Kubernetes to the entire cloud-native ecosystem, Go powers the systems that run the internet. It's not about what you can build - it's about what you won't break at 3 AM. This skill covers idiomatic Go patterns, error handling, concurrency with goroutines and channels, HTTP servers, microservice architecture, and the standard library that makes Go so powerful. Key insight: Go's simplicity is a feature. Fight the urge to abstract. Embrace boring, readable code. 2025 lesson: The teams succeeding with Go are the ones who resist overengineering. A main.go with 500 lines beats a "clean architecture" with 50 packages. Use when "golang, go service, go microservice, goroutine, channels, go http, go api, go backend, gin, fiber, chi router, go concurrency, go, golang, microservices, backend, concurrency, goroutines, channels, http, api" mentioned.
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。
Master the AI tools that generate unlimited content at scale. From stunning images to professional videos, voiceovers to compelling copy - create content that used to require entire teams. Use when "need images, create video, generate content, voiceover, marketing visuals, social media content, ad creative, content, images, video, audio, writing, marketing, creative" mentioned.
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。
Expert in integrating Claude Code with CI/CD pipelines. Covers headless mode for non-interactive execution, GitHub Actions and GitLab CI/CD integration, automated code review, issue triage, and PR workflows. Essential for teams wanting AI-powered automation in their development pipelines. Use when "claude code CI/CD, headless mode, GitHub Actions claude, GitLab CI claude, automated code review, PR automation, issue triage, claude-code, cicd, automation, github-actions, gitlab, headless, pipeline, devops" mentioned.
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。