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概要と使いどころ
Help users master the transition from manual coding to managing AI-driven development workflows by focusing on high-level direction, parallel tasking, and rigorous automated review.
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。
Help users establish high-impact goals that bridge the gap between abstract company vision and daily execution while maintaining radical focus.
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 fast, progressive experiments to map tunable parameters and their effects. Use when optimizing code, prompts, configurations, or other artifacts against a goal or benchmark, or when a long research run needs a planned hypothesis queue, focused trials, and durable findings.
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。
Trigger: PRs over 400 lines, stacked PRs, review slices. Split oversized changes into chained PRs that protect review focus.
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 only after explicit Codex `$superloopy:i-have-adhd` or Claude Code `/superloopy:i-have-adhd` invocation, or when a qualifying leading `loopy`/`루피` task receives Superloopy's non-diagnostic ADHD-friendly output overlay. Do not activate from typos, fragmented writing, urgency, grammar, language proficiency, or ordinary discussion of ADHD, attention, focus, accessibility, or cognitive load.
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 for UI/UX design, product flows, frontend or native interface design, design audits, design translation, asset planning, motion direction, design tokens, or distinctive non-generic apps and websites. Covers web and React, Windows and WinUI/Mica, Apple and SwiftUI, Android and Jetpack Compose/Material, cross-platform UI, and token export. Route to the focused skill, then load only the references required for the selected surface and failure mode.
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 for AI-assisted Unity work that needs live repo discovery, project-derived routing, runtime-owner proof, runtime-visible output hard stops, runtime numeric proof for repeated visible-output failures, state-step guards, multi-agent scope ownership, modular C#/asmdef safety, UI/scene/visual asset gates, data-first content changes, validation, cleanup proof, or durable workflow rules. Best when agents must prove the actual folder/module/scene/prefab/runtime owner before editing, especially runtime UI, generated assets, code graphs, tutorial/state flows, guided selection/action flows, overlay/dim source-bound mistakes, coordinate conversions, focus/highlight/marker/HUD alignment, predictive lead aiming, ballistic trajectories, spatial IoU verification, or repeated "fix still not visible" failures.
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。
A passive daily work journal that Claude keeps FOR you so you never have to write it yourself. Append short entries after meaningful work (what was done, what you focused on, artifacts touched) to 01-daily/journal/YYYY-MM-DD.md. Run a guided reflection at night or in the morning. Use when you run /daily-journal, say "log this to my journal", "add to today's journal", "reflect on today/yesterday", or when finishing a meaningful chunk of work in any session.
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。
Media player traps on Media3/ExoPlayer and desktop engines: crossfade, audio focus, fades, loudness, DSP, queues and shuffle, position restore, service lifecycle, group listening. Use when playback state, queue or audio levels go wrong.
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 when drafting AISTATS author responses or author-reviewer discussion replies under OpenReview, covering text-only discussion, no-link guidance, no revised-paper upload, anonymity requirements, statistician-reviewer pushback patterns, and decision-focused clarification strategy for theory-plus-experiments papers.
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 when drafting the ACM MM (ACM Multimedia) rebuttal — turning multiple anonymous reviews into one focused, anonymous response that fixes factual errors first, adds small confirmatory cross-modal results, concedes calibratedly, and stays inside policy (anonymous, no new external links), written for the area chair who decides.
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 when you need to understand the Academy of Management Review (AMR) developmental, multi-round review and interpret a decision letter focused on theoretical novelty and logical soundness. Explains the process and decision types; it does NOT draft the response document (that is amr-rebuttal).
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 when drafting an ACM CCS rebuttal during the HotCRP author-response window, covering threat-model defenses, adaptive-attack objections, ethics and disclosure questions, anonymity constraints, adversarial reviewer pushback patterns, and decision-focused replies aimed at the meta-reviewer.
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 complete marketing campaign brief from a launch goal, ICP, and product context. Pure reasoning skill. Outputs channel plan, messaging angles, content types, timeline, and success metrics. Designed for seed/Series A founders and small GTM teams who aren't professional marketers but need to run focused campaigns. No scripts — pure reasoning.
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。
Evaluate a website, landing page, content, or any online asset through the eyes of pre-built synthetic ICP personas. Loads personas from buyer-persona-generator output, then runs them against target URLs. Supports three modes: structured scorecard, freeform focus group, and head-to-head competitive comparison. Reusable — run against the same site after changes, or against new content anytime.
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。
Render a 'brand identity reveal' video from a config — a single poster frame in a real, softly-lit space (real wall, soft-focus plant in the corner, dappled leaf shadow, illuminated poster) whose artwork HARD-CUTS through ~10 on-brand poster mockups (hero product, IG post, hanging banners, sticker sheet, logo lockup, poster, two lifestyle stills, packaging, big icon) then holds on a brand end card. The environment plate is one create-image-fal generation; the mockups are real-DOM HTML frame-stepped via Playwright, perspective-composited into the detected frame quad with the plate's real leaf-shadow multiplied back onto each poster (reads as behind glass), sequenced by FFmpeg. Deterministic assembly, FREE (the plate comes from create-image-fal, the bed from create-music-elevenlabs), music bed only and approved brand copy only. Use for the brand-identity-reveal format.
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。
Find newsletters relevant to a target audience/industry for sponsorship opportunities. Discovers newsletters through web search, newsletter directories, and industry research. Returns newsletter name, author, estimated audience, topic focus, sponsorship rates (if available), and contact info.
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。
Resolves GWAS associations to candidate causal variants and credible sets via SuSiE, susie_rss, FINEMAP, CAVIAR, DAP-G, PAINTOR, PolyFun, SuSiEx, MultiSuSiE, and FOCUS. Use when narrowing a GWAS lead SNP to a 95 percent credible set, choosing between in-sample and reference LD, calibrating non-sparse loci with SuSiE-inf or FINEMAP-inf, integrating functional priors via PolyFun, fine-mapping across ancestries with SuSiEx, diagnosing LD mismatch via estimate_s_rss and kriging_rss, handling HLA or long-range LD, or feeding credible sets into coloc.susie for colocalization.
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。
Verify that every interactive control on a page can take keyboard focus and that its primary action fires from the keyboard rather than only the mouse, and say plainly that Tab order cannot be verified today. Use when a component was hand-tested with a mouse, a custom dropdown/modal/combobox was added, or an accessibility report flags an unreachable control.
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 audit SwiftUI, UIKit, and AppKit accessibility for VoiceOver, Voice Control, Switch Control, Full Keyboard Access, Dynamic Type, focus restoration, labels/traits/actions, traversal, custom rotors, NSAccessibility, XCTest checks, adaptive system preferences, and App Store accessibility declarations. Use when implementing accessible UI, fixing an accessibility audit, testing assistive-technology behavior, or substantiating App Store Accessibility Nutrition Labels.
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 when capturing or analyzing ETTrace profiles for a focused iOS launch or runtime flow, including exact-build dSYM UUID matching, Simulator or device capture, processed per-thread flamegraph JSON, sampled inclusive/exclusive time, unresolved symbols, and comparable verification. Use debugging-instruments or swiftui-performance for generic profiling instead.
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。
Optimize App Store product pages for search visibility and conversion. Use for App Store Optimization (ASO), keyword research, app name/subtitle/keyword-field strategy, conversion-focused descriptions and promotional text, screenshot captions and ordering, Custom Product Pages with assigned search keywords, In-App Events, Product Page Optimization tests, localized metadata, ratings/review strategy, and in-app review prompt timing with RequestReviewAction or AppStore.requestReview. Also use when routing ASO vs App Store review, privacy/ATT, or StoreKit implementation boundaries.
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。
Trigger when: (1) User wants to create an educational/explainer video, (2) User has a vague concept they want visualized, (3) User mentions "3b1b style" or "explain like 3Blue1Brown", (4) User wants to plan a Manim video or animation sequence, (5) User asks to "compose" or "plan" a math/science visualization. Transforms vague video ideas into detailed scene-by-scene plans (scenes.md). Conducts research, asks clarifying questions about audience/scope/focus, and outputs comprehensive scene specifications ready for implementation with ManimCE or ManimGL. Use this BEFORE writing any Manim code. This skill plans the video; use manimce-best-practices or manimgl-best-practices for implementation.
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 AI-focused SRE incident response practices for LLM outages, degraded quality, runaway cost events, and safety regressions.
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。