Claude Skills
The open format is called Agent Skills and works in Claude Code, Codex, Cursor and other agents — most people know it as Claude Skills.
Every Agent Skill we could find on GitHub, deduplicated by content. 79 870 files from 1 769 authors, of which 62 217 are unique — the rest is the same skill repackaged into someone else's repository. For each one: what it weighs in tokens, whether it ships runnable scripts, and which MCP servers it needs.
Use huge-plan for open-ended high-risk repo efforts needing websearch during brainstorming and refinement until convergence; exclude direct implementation-only, factual/explanation, trivial, or explicit no-plan requests.
Use plan for normal repo changes needing bounded decisions, refinement, and high-priority review before execution; exclude direct implementation-only, factual/explanation, trivial, or explicit no-plan requests.
MUST USE when investigating a bug, CI failure, test failure, regression, incident, broken behavior, root cause, RCA, or debug-why problem before deciding whether to create an optim-plans solution plan; do not use for ordinary feature ideas, vague product planning, direct implementation-only requests, factual/explanation questions, trivial operations, or explicit no-plan requests.
Use when external research should inform a repo-change plan before implementation; exclude direct implementation-only, factual/explanation, trivial, or explicit no-plan requests.
Use small-plan for small repo changes needing up to three intent checks and exactly one refinement round; exclude direct implementation-only, factual/explanation, trivial, or explicit no-plan requests.
Use when the user asks Codex to review a repository for improvement opportunities, feature inspiration, roadmap ideas, or implementation candidates before planning changes; exclude direct implementation-only, factual/explanation, trivial, or explicit no-plan requests.
Define a multi-agent team for ANY task on ANY system as an explicit deployment topology - pick the shape from the task's dominant risk, specify the runtime/communication/trust layers, place model capability by lane, present it as a diagram + table + trust-boundary note + open choices, and deploy ONLY after the user agrees to the proposed shape. Use when the user asks to "define/design/lay out the team", "what topology are we deploying", "how should the agents be arranged", "design the team for <task>", "what formation for <task>", or wants a team expressed as a topology (nodes, edges, models, trust boundaries) rather than spawned ad hoc. Substrate-agnostic - Cotal mesh, harness subagents, Workflow stages, containers, or any orchestration system.
Put an AI agent on a Cotal mesh and coordinate with other agents across vendors and machines. Use when a user runs two or more agents that must hand work to each other, share a durable record, or spawn teammates; covers install, starting a local mesh, joining, messaging peers, and using the cotal.ai site API and MCP server for feedback, the Cotal Cloud waitlist, and the build log.
Write the brief for a single independent cold reviewer and grade what it returns, keeping it isolated from the panel that already graded the change. Read by whoever AUTHORS the brief; the graded seat never loads this file. Covers what the seat is given, what its verdict binds, who may override it, and how the rules degrade when the vendor set is short. Use when a panel has reached consensus and you want a second opinion consensus cannot anchor, when a change is security-sensitive or hard to reverse, or when you are the author and therefore the worst available reader of your own work.
Run several independent Cotal features concurrently by creating one Git worktree and one spawn-capable mesh manager per feature; each manager staffs a review panel in a dedicated channel, adds one independent cold reviewer briefed under the cold-review skill, owns plan-to-commit delivery, and escalates unresolved product decisions by DM to the coordinator for relay to the user. Use when the user asks to split multiple features across managers/worktrees, run parallel feature teams on Cotal, or have managers create their own review panels.
Create or improve a 32×32 pixel-art persona face for the Frontier Faces demo (examples/04-frontier-faces/personas.mjs) — the animated agent avatars rendered by face-term.mjs / the browser <cotal-face> / the gallery. Use when the user asks to add a new persona/face/avatar, improve an existing one (hair, eyes, likeness, expression), make it "look more like" someone, or fix a face that "doesn't read". Drives the example's own tools (img2rows.mjs, render-png.mjs) and follows FACE-DESIGN.md; uses a multi-agent variant loop for likeness.
Set up Cotal on this machine: install it, start a local agent mesh (NATS + JetStream), verify it, and put an agent on it. Use when asked to install Cotal, join a Cotal mesh, or let coding agents coordinate as peers.
Author and update release notes for Azure App Configuration libraries and providers. USE FOR: write release notes, add release note entry, update release notes, draft release notes, new version release notes, format release notes. DO NOT USE FOR: generating changelogs from git history, writing internal engineering notes.
> 全员通关后把 错题本+笔记本+知识点窗口+wiki 编译成考前速记小抄 cheatsheet.md（每条要点带可溯源 锚点），并在视觉产物模式或用户明确要求 PDF/打印版时按指定页数渲染成打印级 PDF：按「必背结论/公式 → 有难度例题（必要时含题面图）→ 例题解答（代入公式、保留基础过程）→ 要点解释（同类题怎么办）」 四段组织。当复习收尾、用户要「考前小抄/速记/总结/打印版」时使用。
> 备考教练的一屏速查卡：工作流、3×4 学习选择、产物偏好、工作区文件、6 大题型、来源规则与子技能路由。 用户问怎么用、有哪些模式、文件用途或支持题型时使用。
> 临考前的极速备考总教练。把课件、大纲、重点与真题建成分章 wiki 和标准题库，再组织惰性授课、 题库判分、错题与疑难复盘及可选考前小抄，并持久化进度。用于期末、备考、突击、刷题、划重点、 错题与考前复习；不用于长期规划或与考试无关的写作/编程。
教学过程中自动捕获和记录学习者的概念疑难点（"为什么/是什么/怎么推/什么意思"类型的问题），保存到进度文件的"概念疑难点记录"区，形成考前回顾清单。
帮助学生在临考前进行结构化极速复习：解析课程资料/大纲/重点，按章节生成 wiki 知识库与标准题库，组织针对性刷题与判分，并记录复习进度和错题。当用户即将考试、需要快速复习计划、练习题、错题复盘或考前小抄时使用（关键词：期末/备考/复习/刷题/划重点/错题；exam, cram, study plan, quiz, review）。不适用于长期学习规划、与考试无关的写作或编程任务。
> 只读检查一个已生成的备考工作区是否健康并报告问题，默认不做任何修改。核对 .ingest 原材料版本、 内容单元、接管队列与派生产物完整性，以及 wiki、题库、视觉证据、计划和进度的一致性。当用户怀疑 工作区有问题、建库 readiness 被阻断、或想在开始复习前体检时使用。
> 从学生上传的课件/大纲/老师勾的重点/真题，一键初始化并验证备考工作区：解析 PDF、DOCX、PPTX、 XLSX、常见独立图片与 txt/md，建立分章节 LLM Wiki、标准题库、结构化接管队列与进度状态；仅在 Python 确实无法运行时 明确降级为手动写盘。当工作区尚未建立、资料发生变化、或建库 readiness 被阻断时使用。
> 从 references/quiz_bank.json 抽取本章题目并按标准答案判分，支持选择、主观、画图、填空、判断、代码； 主观题按 keywords 要点覆盖判分，连续错两次提供提示/跳过/归档。禁止现场编题。用于阶段检查或模考。
> 按章节惰性加载授课：每次只读当前阶段的一个 wiki 章节，用生活隐喻讲概念、解剖公式；重点题固定走 题面图→问题→读图量→公式→演算→答案详解→溯源七步，画图题先运行算法。用于讲懂当前章或老师勾出的重点题。
将已经讲完但尚未完成阶段门禁的一个章节整理成强类型教材清单，并在视觉模式下编译为公式可读、图片可见、知识点与全部对应例题逐项精讲的自包含 HTML/PDF。结构化工作区准备阶段完成证据、用户说 Markdown 公式仍是 raw LaTeX、图片缺失、要含课件/作业/Quiz/模拟考试题及答案的零基础讲义，或要求打印版时使用。
> 考前复盘已记录错题与概念疑难：重做原题、复述疑难、更新已订正/已回顾/待回顾状态，并形成最后扫雷清单。 进入最终复习阶段或用户要求复盘、查漏补缺时使用。
| 实习.skill / get-job.skill：从岗位调研、简历改写到分轮次面试准备的全流程求职 skill。适合找工作、投实习、校招、秋招、春招、暑期实习、社招、跳槽、转行、跨专业求职、留学生求职，以及产品经理、运营、市场、咨询、AI 产品、AI Coding、数据分析、技术岗等目标岗位准备。 核心能力：① WebSearch 调研公司、岗位 JD、业务线、竞品、面经、招聘流程和隐性门槛；② 按目标岗位反向定位简历，做 JD 匹配、ATS 关键词、经历筛选、STAR/CAR 改写、可迁移能力翻译、docx 简历生成；③ 按真实轮次准备面试，覆盖一面/业务面/专业面/主管面/HR 面/recruiter screen 等已确认或高置信轮次，逐条深挖简历 bullet、项目逐字稿、自我介绍、表达训练、模拟面试、反问清单、面后复盘题库。 适用于「改简历」「简历优化」「简历润色」「简历匹配 JD」「求职简历」「投递前改简历」「按岗位改简历」「准备面试」「面试准备」「面经分析」「模拟面试」「自我介绍」「项目经历怎么讲」「简历被追问怎么办」「双非拿大厂 offer」「背景不对口怎么办」「AI 产品实习」「运营实习」「产品经理校招」等场景。 质量保障：不编造经历、不改背调硬信息；所有强 claim 做证据化审计；搜索源按市场和 A/B/C/D 分级；轮次不写死；最终交付前必须跑质量闸门和覆盖矩阵，避免漏 bullet、标签泄漏和过度包装。
Build AI agents with the Strands Agents SDK - the open-source framework (the agent "brain") for writing agent logic, tools, and multi-agent systems in Python. Model-agnostic, AWS Bedrock by default. Covers Agent, the @tool decorator, model providers (BedrockModel), multi-agent patterns (agents-as-tools, Swarm, Graph), conversation management, and streaming. Every import verified against official Strands docs. To DEPLOY a Strands agent on AWS, use the aws-harness skill. Triggers on Strands, Strands Agents, Strands SDK, agent framework, agents as tools, Swarm, Graph multi-agent, BedrockModel.
Build a premium cinematic landing page with mouse-scrub video hero and brand-driven narrative-arc sections. Use whenever the user provides a hero video plus a product / subject / brand and wants a landing page, promo site, product showcase, marketing page, or storytelling site. Works for any language (RTL or LTR — Hebrew, English, Arabic, Spanish, French, Japanese, etc.) and any subject (food, tech, animals, fashion, services, SaaS, wildlife campaigns, music releases, books, real estate). The signature effect is mouse-driven video scrubbing — the hero video lives across the entire page as a fixed backdrop, and moving the mouse left-right scrubs the video timeline so the subject responds to the cursor. Below the hero, 4-5 fully-opaque sections each carry their own brand identity (color, typography emphasis, layout pattern) and walk the viewer through a narrative arc (e.g. longing → joy → nostalgia → contemplation → action). Triggers on phrases like "build a landing page from this video", "cinematic landing page", "mouse scrub hero", "video that follows the cursor", "Apple-style premium product page", "the baby video scrub thing", "narrative landing page", "scrubable hero", "golden landing template", "make a promo site for this brand", "build me a showcase page with this clip". Do NOT use for parallax frame-scrub landings where the page itself doesn't scroll (use `parallax-landing-page` instead) or for video editing / captioning workflows (use `video-edit`).
Build a new AI agent on AWS and deploy it easily, OR wrap and deploy an agent you already have, using the Amazon Bedrock AgentCore harness. Explains what an "agent harness" is (the runtime scaffolding around a model - agent loop, tool execution, memory, identity, observability), then gives two fully-working, verified paths - (A) scaffold + ship a new agent with the AgentCore CLI (create/dev/deploy/invoke), and (B) deploy a prepared agent (Strands, LangGraph, or custom) via the SDK wrapper or a FastAPI + Docker + ECR container. Every import and command is verified against official AWS/Strands docs. Use when the goal is to create, wrap, or deploy an agent on AWS AgentCore. Triggers on agent harness, AWS harness, AgentCore, AgentCore CLI, agentcore create, agentcore deploy, deploy agent on AWS, bring your own agent, Bedrock AgentCore runtime, serverless agent.
Award-winning director's brain for making films/videos with AI. Runs a gated, interrogation-first process: lock the IDEA and the SCRIPT (the story) in words before generating a single pixel, then plan shots/camera/light/sound, then generate and edit. Use whenever creating a video, film, teaser, trailer, promo, ad, short, reel, documentary, or narrative piece AND the storytelling must actually work — or any time the user says the story/script keeps failing. Hebrew triggers: סרטון, טיזר, פרומו, פרסומת, ריל, סרט, תסריט, סטוריבורד. Handles development, story, and shot-planning; composes with cinematic-ai-video and yuv-fomo-teaser (style/manipulation), hyperframes (render), nano-banana-2/ElevenLabs (assets). Backed by a 28-chapter Director's Bible in references/.
Interact with all Google Workspace APIs via the gws CLI. Use when managing Drive files, sending/reading Gmail, creating Calendar events, reading/writing Sheets/Docs/Slides, managing Chat spaces, contacts, Admin users/groups, Vault eDiscovery, Classroom, Apps Script, Workspace Events, or configuring the gws MCP server. Triggers on Google Workspace, gws, Drive, Gmail, Calendar, Sheets, Docs, Slides, Chat, Tasks, Meet, Forms, Keep, Admin, People, Vault, Classroom, Apps Script, Cloud Identity, Alert Center, Groups Settings, Licensing, Reseller, Model Armor, gws CLI, gws mcp, Google API, Workspace automation, npx skills add.
Detect installed AI coding agents and append honest-feedback rules to their instruction files. Scans for config files (CLAUDE.md, copilot-instructions.md, .cursorrules, etc.), adapts output format per agent, and appends directives that disable sycophancy and enable constructive pushback. Use when setting up honest feedback, disabling people-pleasing, or enabling objective criticism. Triggers on honest agent, objective feedback, no sycophancy, honest criticism, contradict me, challenge assumptions, honest mode, brutal honesty.
Master prompt-engineer for photoreal, artifact-free AI still images on ANY tool (Reve, Midjourney, Flux, GPT-image, Imagen, Nano Banana, Stable Diffusion). Builds prompts that hit National-Geographic-grade realism — true skin/fur texture (no plastic), correct anatomy/hands/faces, physically coherent light/shadows/reflections, clean legible text — while engineering deliberate visual IMPACT (color contrast, composition, awe/adrenaline, a striking point of view). Runs a gated process: lock the point-of-view and build the 8-block Capture Stack BEFORE generating, then run a forensic pre-submit inspection against the known artifact list. Use whenever the goal is a single still image that must look REAL and hold up under close inspection — contest entries, hero shots, product/character/wildlife/architecture/concept art, or any time AI images come out plastic, distorted, or fake. Composes with nano-banana-2 (execution) and director (motion). Hebrew triggers: תמונה, תמונות, פוטוריאליזם, ריאליזם, לייצר תמונה, פרומפט לתמונה, בלי עיוותים, עור פלסטיק, ידיים מעוותות, פרצוף מעוות, חדות, נשיונל ג'יאוגרפיק.
Pull, analyze, manage, and CREATE Meta ads (Facebook, Instagram, Messenger, Threads, Click-to-WhatsApp) via the Marketing API. Use when the user mentions Meta/FB/IG ads, Ads Manager, ROAS, CPA, CPM, CTR, ad spend, campaign or ad set performance, creative fatigue, frequency, CTWA, audience/placement breakdowns, A/B ad tests, or wants to pause an ad, change a budget, duplicate a winner, or launch a new campaign from scratch. Trigger on Hebrew terms like פרסום בפייסבוק/באינסטגרם, פרסומות מטא, ביצועי קמפיין, פרסומות, צור קמפיין, השק קמפיין, A/B טסט. Trigger on questions like how are my ads doing, which creative is winning, is my ad fatigued, what's my CPA, drop a 30-day report, launch an A/B test for my course, build a campaign with these 3 angles. Trigger even if auth isn't set up — the skill walks through one-time setup. Do NOT use for organic Instagram analytics, Reels view counts on non-promoted posts, or organic Threads engagement; those need the Instagram Graph API.
Build a scroll-driven cinematic landing page from a short video. The user provides a 5–15 second video (often AI-generated); this skill extracts every frame at HD JPEG quality, then produces a single-hero HTML page where the user's scroll gesture scrubs the frames in place (the page itself never scrolls) and 5 dramatic text overlays crossfade in/out — Google Anton headlines, Caveat handwritten accents, locked body, virtual scroll. Use this skill whenever the user wants to "turn this video into a landing page", "make a scroll-scrub landing page", "build a parallax hero from this clip", "add a new landing page to the parasites showcase", "do the same as github/lion/hope for this new video", or any variant that pairs a short clip with dramatic scroll-triggered storytelling. Trigger even if the user only says "use my video for a landing page" — that is this skill.
Edit any video into a captioned showcase — transcribe (any language, defaults to large-v3), present a transcript_review.txt for the user to fix mishears BEFORE rendering, then build a HyperFrames composition with liquid-glass caption pills, liquid blob background, liquid morph wipes, optional behind-subject text via background removal, and render the final video. Use whenever the user provides a video file and asks to edit it, caption it, add subtitles, fix existing captions, make a reel/promo/captioned tutorial, or "do the same" pattern as a prior captioned video. Supports English, Hebrew, and any Whisper-supported language. **Renders both 16:9 (YouTube / horizontal) and 9:16 (TikTok / Instagram Reels / YouTube Shorts) from the SAME 16:9 source** — vertical mode uses a centered footage strip with a blurred backdrop + liquid blobs and a vertical-tuned caption pill, no need to re-shoot. THE PIPELINE PAUSES FOR USER APPROVAL on the transcript before final render — this is the support mechanism for getting captions perfect (especially Hebrew). Pairs with hyperframes, hyperframes-cli, hyperframes-registry, and yuv-design-system skills.
Turn any video into a cinematic scroll-driven landing page — Apple-style hero where scrolling progresses the visible frame through the video. Use when the user provides a video file and asks for "a landing page from this video", "scroll-frame website", "Apple-style scroll site", "hero that scrubs the video", "like the GitHub Copilot landing", or any equivalent. Extracts N evenly-spaced frames via ffmpeg, builds a self-contained HTML page with a sticky hero + JS scroll listener that swaps the visible frame as you scroll, plus headline, sections and CTA below. For YUV.AI projects, applies the yuv-design-system skill in Neon mode (pink/cyan/white, default for YUV.AI web) — Decks (purple/yellow) is reserved for slides only. For generic / non-YUV.AI projects, picks an appropriate palette per the source video. Output is one folder with `index.html` and a `frames/` directory — drop on any static host.
Build accessible web applications following WCAG guidelines. Use when implementing ARIA patterns, keyboard navigation, screen reader support, or ensuring accessibility compliance. Triggers on accessibility, a11y, WCAG, ARIA, screen reader, keyboard navigation.
X (Twitter) data extraction and scraping. Use when asked to scrape tweets, extract followers, search Twitter/X users, download media from tweets, monitor X accounts, or analyze Twitter engagement. Triggers on twitter, x.com, tweet, follower, following, retweet, quote tweet, scrape, OSINT.
Build cinematic, narrative-driven presentation decks in Yuval Avidani's signature style using @open-slide/core. The user describes a topic and audience; this skill scaffolds an open-slide project, drafts the 4-act narrative arc (Boarding → Ascent → Cruise → Descent), writes every slide in the Yuval voice (plain-language, no jargon, story-driven), applies the brand visual language from yuv-design-system, and orchestrates companion skills for hero images and video moments. Triggers on "make a deck", "create slides", "build a presentation", "build a deck", "new deck", "presentation about", "talk deck", "hackathon deck", "open-slide deck", "yuv-decks", "yuv deck", "deck like Yuval", "מצגת", "שקפים", "דק", "מצגת על", "להכין מצגת". Use proactively whenever the user asks for ANY slide-based talk; the skill self-selects the right scope.
> Generate unified, on-brand Instagram Reel covers for Yuval (YUV.AI Neon Phoenix system) — the signature look is a giant Hebrew headline BEHIND the subject cutout + a punch line IN FRONT (depth effect), on rich black with a dim neural-net field, series-colored chip + phoenix mark. Use whenever Yuval asks for an Instagram/Reel/TikTok/YouTube cover, thumbnail, עטיפה, קאבר, תמבנייל, cover image for a video, or wants his Instagram grid to look consistent. One command per cover; background removal included in the pipeline.
Yuval Avidani's YUV.AI brand and design system. Apply ONLY when YUV.AI-branded output is requested — presentations, decks, keynotes, portfolio, brand site, profile, speaker bio, brand assets, or any prompt mentioning YUV.AI / "my brand" / "my deck" / "my site" / "for me". Do NOT auto-trigger on generic "build a game / web app / dashboard / landing page" without YUV.AI context — those use whatever palette fits. Three modes; NEON (hot pink #FF1464 + neon cyan #00E5FF + white, DEFAULT for YUV.AI web, apps, games, dashboards, social, general visual work); DECKS (Fly High purple/yellow/grey, presentations and slides ONLY); Warm Editorial (pink/yellow/bone for Hope, Marcus, bigcats.ai, practical.yuv.ai). Universal Fly High throughline across all modes; flight/progress motifs (HUD strips, dials, "Let's Fly High" tagline, phoenix mark). Anton + Inter (EN), Rubik + Assistant (HE), letter-spacing 0 default. Bundled brand assets, canonical socials, credentials. Project brand wins if specified.
Top-of-pyramid orchestrator for Yuval Avidani's YUV.AI brand work. Apply when (a) the user wants YUV.AI output and the medium is ambiguous or multi-medium, (b) the user is planning a launch or cross-channel campaign for YUV.AI, or (c) explicitly invokes /yuv-pilot or asks "what should I build for YUV.AI / my brand". Triggers: "for YUV.AI", "for my brand", "YUV.AI launch", "ship something for me", "orchestrate", "cross-channel", "multi-platform for me", "yuv-pilot", Hebrew השקה, מולטי-פלטפורמה ל-יובל. Does NOT do the work — it identifies the right downstream YUV.AI skills (yuv-design-system across 3 modes, yuv-decks for slides, yuv-viral-video for short MP4s, hyperframes for HTML→MP4, nano-banana for in-brand imagery, gsap for animation), explains the composition, hands off. Does NOT apply to non-YUV.AI requests. When a request is clearly single-medium (just a deck, just a viral short), the specific skill wins — yuv-pilot is the front door for ambiguous or multi-output requests.
> Yuval's all-in-one AI video pipeline. Turns an idea/script into a finished, on-brand MP4 by orchestrating HyperFrames (HTML→deterministic video render), Lottie (branded motion graphics), ManimCE (math / neural-network / concept animations), and a transcribe→approve caption flow — all wrapped in the YUV.AI Neon Phoenix brand via a frame.md. Use whenever Yuval wants to make, about X", "explain X as a video", "neural network animation", "turn this into a video", hyperframes, animation, "make a video", "explain ... as a video", מצגת וידאו, סרטון, הסבר וידאו. Routes each beat to the right engine, wraps in brand, self-verifies, and renders.
Edit any selfie or screen-share footage into a viral short-form video in YUV.AI's signature style — Apple-style liquid-glass cards (real CSS backdrop-filter), dark-mode polish, MrBeast-paced cuts, video-title karaoke captions, premium GSAP motion graphics, no fake content, never covering the speaker's face. Hebrew is rendered in Rubik Black, English in Anton uppercase. Always renders BOTH 9:16 and 16:9 and always saves with _V<N> suffix for backups. Trigger when the user drops a path to an .mp4/.mov/.mkv and says "edit this", "make it viral", "turn this into a short", or any Hebrew equivalent (ערוך סרטון, סרטון ויראלי, להפוך לוויראלי, ריל, שורט). The pipeline is the COMBINATION of two skills: video-use (transcription + word-snapped cuts + base extraction) and hyperframes (HTML/CSS/GSAP visual composition + render). Do NOT use for podcast-only audio edits.
>- Submit an azd template to the awesome-azd gallery. Use when asked to submit, add, or contribute a template to awesome-azd. Requires only a GitHub repository URL — all metadata (title, description, languages, frameworks, Azure services, IaC) is auto-detected by the submission pipeline.
Build, lint, test, and verification workflow for the portal-tunnel Go+frontend monorepo. Use when setting up the repo, running CI-equivalent checks, or before committing changes.
How the portal-tunnel client CLI (cmd/portal-tunnel) is structured and invoked — expose/agent/list/update subcommands, flags, validation rules, and x402/routing options. Use when changing or testing client-side tunnel behavior.
Full environment-variable / flag reference for configuring the portal-tunnel relay-server (cmd/relay-server), plus how config is embedded and how Docker/Compose deploys it. Use when configuring, deploying, or debugging a relay.
How to build and run the portal-tunnel relay-server locally for HTTP/browser testing of the embedded SPA frontend and admin/policy APIs.
Where things live in the portal-tunnel repo (sdk/portal/types/utils/cmd/discovery/x402/frontend/extensions) and where new code belongs. Use when locating functionality or deciding where to add code.
Expose, preview, protect with x402 payments, or keep a local web app, static site, HTTP route set, or explicitly requested TCP/UDP service reachable through Portal, then verify the public endpoint and report its lifecycle. Use when the user asks to deploy, publish, share, tunnel, expose, create a public preview, add a paid route, or configure x402 for a local app with Portal. Do not use for deploying a Portal relay, generic cloud hosting, or publishing this plugin.
Best practices and idiomatic patterns for SwiftUI. Use when writing, reviewing, or editing SwiftUI code.
New SwiftUI APIs, behaviors, and deprecations introduced in the 2027 OS releases (iOS 27, macOS 27, watchOS 27, tvOS 27, visionOS 27). Use when a SwiftUI view using @State fails to compile with \"used before being initialized\", \"invalid redeclaration of synthesized property\", or \"extraneous argument label\" errors after an SDK update (@State migrated from a property wrapper to a macro in SDK 27; the obvious fix of reordering init assignments is WRONG and produces incorrect runtime behavior; you MUST consult this skill's references before answering); when @ViewBuilder or @ContentBuilder code hits ambiguous overloads in overlay/background or type-check performance regressions after an SDK update; when the user asks what's new in SwiftUI (generally, or for a specific 2027 platform); when adding drag-to-reorder to any container (List, LazyVStack, LazyVGrid, stacks, or custom layouts) via reorderable()/reorderContainer, including the drag-and-drop that integrates with it (dragContainer, dropDestination), or combining items by dropping one onto another; when working with AsyncImage loading and caching (images reloading when scrolling back, the default HTTP cache, a per-request cache policy via AsyncImage(request:)/URLRequest, or applying a custom URLSession with asyncImageURLSession); when adding swipe actions to rows (swipe-to-delete or other swipe actions) in a ScrollView, LazyVStack, LazyVGrid, or stack and not just List, via swipeActions()/swipeActionsContainer(); when working with toolbars, such as controlling which items stay visible versus move into the overflow menu when space is constrained or buttons get cut off (visibilityPriority, ToolbarOverflowMenu), pinning an item so it never overflows (topBarPinnedTrailing), minimizing the navigation bar or toolbar on scroll (toolbarMinimizeBehavior), generating toolbar items with ForEach, or hiding the status bar via the statusBar toolbar placement; when presenting a confirmation dialog or alert from an optional item binding (the sheet(item:) shape) so it shows when the bound value becomes non-nil and passes the unwrapped item into the actions and message closures; when building or migrating a document-based app (including read-only document viewers), reading or writing files through DocumentGroup, optimizing autosave performance for package documents, accessing the document's file URL directly (for example to hand to AVFoundation, PDFKit, Core Image, or any C library that takes a path), reporting progress from a save or load, or migrating from FileDocument / ReferenceFileDocument; or when resolving other SDK 27.0 source incompatibilities and deprecation warnings (for example statusBarHidden on visionOS).
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Verify iOS app behavior on device or simulator via screenshots, UI hierarchy, and touch interactions.
Modernize test suites to use modern Swift Testing features or migrate from XCTest.
| Guide for the C -fbounds-safety language extension. Covers the language model, pointer annotations, adopting bounds-safety in existing C code, compiler build settings and modes, and runtime debugging of bounds violations.
Modernizes UIKit apps for multi-window environments by replacing legacy shared-state APIs with context-appropriate modern alternatives. This includes references to mainScreen, interfaceOrientation, application and scene lifecycle, as well as safe area inset updates.
Claude Skills — questions
Answers built from the skills we actually parsed.