Solves UI lock-in. Reverse engineers your existing UI, strips all layout/token decisions, preserves every hook, handler, and API call untouched, then rebuilds the UI from scratch with a fresh design system. Use /ui-restructure to fully redesign, --style apple|linear|minimal|dashboard for named styles, --mode layout|theme|grid for partial rebuilds, --god-mode to redesign from the user's perspective using 100-user mindset simulation and 6 UX principles, --keep-tokens to preserve your token system, --prompt for custom redesigns. Applies mandatory world-class polish: spring motion, 5-state micro-interactions, 8pt spacing grid, WCAG accessibility. Supports Next.js, React, Vue 3, Tailwind, CSS Modules, styled-components, shadcn.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
vamsivarma27/ui-restructure☆ 62026년 8월 24일 업데이트
Draft English scientific manuscript sections and initial submission materials from author-provided evidence. Use it to organize claims and supporting results, restructure arguments, or shorten the main text while adapting the draft to the paper type and target journal.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Draft an abstract or introduction from research notes
- Restructure the argument in Results and Discussion
- Shorten the main text and allocate supporting details
Yuan1z0825/nature-skills☆ 4.9만2026년 10월 19일 업데이트
Restructure existing code without changing its behavior, through a test-gated refactoring loop: a named target, a green suite over that target before any edit, a planned sequence of small named refactorings, and the full suite re-run after every step. Use when the user wants to refactor, restructure, clean up, simplify, or improve the design of existing code, or to apply refactoring recommendations from a code-review or architectural-analysis report. This skill changes code; it does not review code (use code-review), assess architecture (use architectural-analysis), plan a multi-module restructure before executing it (use plan-a-change), map domain boundaries before restructuring along them (use ddd-analysis), or build new behavior test-first (use tdd). Do not use it on code inside an active tdd loop; the refactor step of tdd owns that cleanup. Runs its planned sequence to completion without pausing for review; to review each named refactoring as it lands, use pairing.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
testdouble/han☆ 3162026년 10월 17일 업데이트
Restructure code through extraction, consolidation, or responsibility moves while preserving its behavior. Establish checks before editing, repeat them afterward, and keep intermediate versions buildable and testable without mixing in feature changes.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Extracting code while preserving behavior
- Consolidating duplicate processing
- Moving responsibilities between modules
JuliusBrussee/caveman☆ 11.4만2026년 10월 18일 업데이트
Organize Confluence documentation with clear page hierarchies, reusable templates, and access plans. Create and update pages, embed Jira reports, and audit existing content to identify outdated material and establish review responsibilities.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Restructure a team's Confluence space
- Standardize meeting notes and decision logs
- Embed Jira issues and charts in documentation
alirezarezvani/claude-skills☆ 2.8만2026년 8월 30일 업데이트
Plan organizational changes such as tool migrations, restructures, and strategy shifts using ADKAR, a five-stage model for adopting change. Structure communication, training, and follow-up while addressing employee concerns, resistance, and fatigue from overlapping changes.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Plan communication and training for a tool migration
- Prepare reorganization announcements and employee FAQs
- Explain a strategy shift and its impact on teams
alirezarezvani/claude-skills☆ 2.8만2026년 8월 30일 업데이트
Analyze and update connected Google Sheets using precise tabs and cell ranges. Find spreadsheets, search rows, clean tables, repair formulas and charts, or create a new spreadsheet from data or an existing template.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Clean and restructure an existing table
- Repair formulas and charts
- Create a spreadsheet from a template
openai/plugins☆ 7.5천2026년 10월 8일 업데이트
Restructure an academic paper's title and section structure to match a target journal's house style. Asks the user to specify the target journal first, then adjusts main.tex accordingly (title wording and case, section skeleton, heading case, numbering scheme, merging/splitting sections). Trigger when user says "paper style" / "paper-style" / "期刊风格" / "按目标期刊调整" / "调整为XX风格" / "JFE风格" / "convert to journal style" / "restructure for [journal]", or wants a paper's title/sections reformatted for a specific journal submission.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
brycewang-stanford/Auto-Empirical-Research-Skills☆ 4.7천2026년 10월 15일 업데이트
Design any process, idea, problem, or body of knowledge into an ICM (Interpretable Context Methodology) workspace — folder structure as agent architecture — or restructure an existing folder, repo, or vault into one. Use when the user wants to (1) turn a recurring workflow into an agent-runnable folder pipeline, (2) organize scattered notes, files, or knowledge into a library one AI agent can walk, (3) map a team or company as connected context ("context map", "second brain", "team brain", "knowledge base for AI"), (4) audit a codebase or mixed folder into a walkable edit map (objects, processes, change-impact) so later agents can change it without slurping the tree, (5) audit or restructure an existing workspace to ICM conventions, or (6) says "make this an ICM", "ICM this", "map this repo", "audit this folder", "what would a change hit", "build me a workspace", or "structure this for agents".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
RinDig/icm-architect☆ 2천2026년 10월 14일 업데이트
Write code through a disciplined, BDD-framed Test-Driven Development loop: build a behavior test list, then drive each behavior through red-green-refactor with an enforced observed-failure gate. Use when the user wants to implement, build, or write code test-first, "do TDD", follow "red-green-refactor", drive code from tests, choose the next test by the Transformation Priority Premise (TPP) or ZOMBIES ordering, or grow a feature behavior-by-behavior with tests leading. This skill writes and changes code; it does not produce a test plan document (use automated-test-planning, or manual-test-planning for a plan a person runs by hand), review or audit existing code (use code-review), restructure existing code outside a TDD loop (use refactor, or plan-a-change to plan a multi-module restructure), specify what a feature should do (use plan-a-feature), or find the root cause of a bug (use investigate). Runs its loop to completion without pausing for review; to review each behavior as it lands, use pairing.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
testdouble/han☆ 3162026년 10월 17일 업데이트
Plans an architecture-driven change to code that already exists: module boundaries, type responsibilities, layering, coupling, and the public surface a revision moves. Produces a buildable change plan that names the types, modules, and methods involved and records the surface delta each change makes. Use when the user wants to plan, scope, or sequence a restructure, extraction, split, consolidation, responsibility shift, or API revision of existing code, including "these responsibilities are wrong, plan the fix". Does not assess an area and stop at findings — use architectural-analysis. Does not specify new behavior — use plan-a-feature. Does not diagnose a bug — use investigate. Does not write the code — use refactor to restructure it or tdd to build it.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
testdouble/han☆ 3162026년 10월 17일 업데이트
Applies Han's shared Human-Readable Output Standard to a target you already have — a file on disk, text pasted into the prompt, or a draft already produced in the conversation — by dispatching the readability-editor to rewrite its prose so the main point comes first, headings are descriptive, each paragraph carries one idea, and sentences stay short and active, while preserving every fact. Use when you want to make a document or draft readable, edit or polish prose for readability, clean up writing, tighten wording, or re-apply the readability standard to something already written. Rewrites prose only, leaving code, diagrams, and citation identifiers unchanged. Does not write new feature or system documentation — use project-documentation. Does not restructure code or review it — use refactor to restructure code and code-review to audit it. Does not judge the underlying work or raise findings; it only rewrites the writing.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
testdouble/han☆ 3162026년 10월 17일 업데이트
Audit a whole regression suite and prune/restructure it with evidence: per-test coverage fingerprinting, AST near-duplicate clustering, CI-history mining for never-failing and flaky tests, prune decision rules (redundant/obsolete/low-value/keep), smoke/core/extended tiering by risk and defect-detection history, and a defensible "what we deleted and why" record. Deletion is destructive — quarantine and human sign-off are mandatory. Use when: "audit the test suite," "prune redundant tests," "find duplicate tests," "which tests can we delete," "restructure into smoke/core/extended," "is this test pulling its weight," "shrink the regression suite." Not for: Judging whether an individual test is WELL-WRITTEN (smells, assertions) — that is ai-qa-review. Healing one flaky test at runtime — that is test-reliability. Bulk selector regeneration after a UI refactor — that is selector-drift-recovery. Related: ai-qa-review, coverage-analysis, test-reliability, risk-based-testing, qa-project-context.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
petrkindlmann/qa-skills☆ 1942026년 6월 11일 업데이트
Optimize existing blog posts and web content for GEO (Generative Engine Optimization) — AI search visibility on ChatGPT, Perplexity, Claude, and Google AI Overviews. Use whenever a user provides a blog URL or pastes existing content and asks to optimize it for AI search, rewrite for LLM visibility, improve GEO score, make content answer-first, add FAQ sections, restructure headings for AI retrieval, improve citation potential, or audit content for AI readiness. Also triggers on "GEO optimize this", "make this AI-search ready", "rewrite for Perplexity", "optimize for ChatGPT", "optimize for Google AI Overviews", "improve AI visibility", "reformat for AI search", "make this content citation-worthy", "content isn't showing up in AI search", "why isn't my blog cited by AI", "GEO audit", "answer-first rewrite", "restructure for AI", "make my blog AI-friendly", "improve LLM citability". Do NOT trigger for writing new content from scratch — use geo-content for that.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Infrasity-Labs/dev-gtm-claude-skills☆ 1412026년 6월 29일 업데이트
Frontend structure worker: SCAFFOLD new React project or RESTRUCTURE existing monolith to component-based architecture
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
tensology/decisionsai☆ 172026년 10월 15일 업데이트
에이전트 스킬을 새로 만들거나 수정하면서 호출 조건, 작업 절차, 부속 파일 배치를 정리합니다. 설정과 참조 경로, 변경한 보조 스크립트도 검증합니다.
- 반복 작업을 스킬로 만들 때
- 기존 SKILL.md를 수정할 때
- 부속 자료와 스크립트를 정리할 때
openclaw/openclaw☆ 39.2만2026년 10월 19일 업데이트
반복하는 LLM API 요청에서 공통 지시와 자료를 캐시로 재사용하기 쉽게 배치합니다. 캐시 사용량, 읽기·쓰기·저장 비용과 응답 시간을 확인해 구성을 검토합니다.
- 반복 API 요청의 공통 지시를 재배치합니다
- 캐시 읽기·쓰기·저장 비용을 계산합니다
- 캐시 사용률과 응답 시간을 측정합니다
affaan-m/ECC☆ 28.4만2026년 10월 16일 업데이트
Coordinate code refactoring, restructuring code while preserving its behavior. Check existing tests before changes, work in small steps, review the result, and pause for approval of the plan and before committing.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Extracting a module without changing behavior
- Removing duplicate or unused code
- Reducing nesting and clarifying names
affaan-m/ECC☆ 28.4만2026년 10월 16일 업데이트
Restructure claude-flow v3 into focused modules using Domain-Driven Design, which groups code by responsibility. Define module boundaries, event communication, and plugin interfaces to support a modular architecture with independently testable business logic.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Split an oversized orchestrator into focused modules
- Define boundaries between tasks, sessions, and monitoring
- Design plugin extensions and domain events
ruvnet/RuView☆ 9.9만2026년 10월 19일 업데이트
Restructure claude-flow v3 into focused modules using Domain-Driven Design, which groups code by responsibility. Define module boundaries, event communication, and plugin interfaces to support a modular architecture with independently testable business logic.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Split an oversized orchestrator into focused modules
- Define boundaries between tasks, sessions, and monitoring
- Design plugin extensions and domain events
ruvnet/ruflo☆ 7.7만2026년 10월 19일 업데이트
Guides code cleanup and restructuring by mapping dependencies, assessing test coverage, and planning small changes. Supports tasks such as extracting functions or renaming symbols, with checks after each step and recovery when verification fails.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Extracting validation logic into a separate module
- Renaming symbols across related files
- Simplifying conditionals and repeated patterns
code-yeongyu/oh-my-openagent☆ 7만2026년 10월 19일 업데이트
Create, edit, and clean spreadsheet files, including Excel workbooks and CSV data. Build formulas and formatting with openpyxl, a Python library, then recalculate and validate workbooks to check for formula errors and file problems.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Create a workbook with formulas and formatting
- Edit an existing spreadsheet
- Restructure messy CSV or TSV data
asgeirtj/system_prompts_leaks☆ 7만2026년 10월 16일 업데이트
Plan a website's pages, hierarchy, navigation, URLs, and internal links. Produce page trees, visual sitemaps, URL tables, and navigation specifications to guide a new site or reorganize an existing one around visitor needs and business goals.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Plan the page structure for a new website
- Reorganize navigation on an existing site
- Design URLs and internal links for a blog section
coreyhaines31/marketingskills☆ 5.5만2026년 10월 16일 업데이트
Organize PyTorch models and data pipelines with PyTorch Lightning, automate training, save checkpoints, and track experiments. Includes templates and guidance for configuring training across multiple GPUs or TPUs.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
- Restructure PyTorch training code into LightningModules
- Build reusable data preparation and loading pipelines
- Configure checkpoints, early stopping, and experiment logs
K-Dense-AI/scientific-agent-skills☆ 5.3만2026년 10월 16일 업데이트