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概要と使いどころ
Make a primary button feel alive by gently pulling it toward the cursor as it approaches, then springing back. Keep it subtle and reserve it for one or two primary actions. Disabled on touch and under prefers-reduced-motion. Do not use it on dense UIs full of buttons.
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 floating action button that morphs open — Lottie JSON. A Lottie (JSON) animation — portable motion that plays identically on web and app via lottie-web. Honors prefers-reduced-motion (don't autoplay). Reserve Lottie for motion that earns its ~160KB runtime.
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。
An animated pagination dots indicator — Lottie JSON. A Lottie (JSON) animation — portable motion that plays identically on web and app via lottie-web. Honors prefers-reduced-motion (don't autoplay). Reserve Lottie for motion that earns its ~160KB runtime.
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 heart/favorite icon that animates on toggle — Lottie JSON, portable across web & app. A Lottie (JSON) animation — portable motion that plays identically on web and app via lottie-web. Honors prefers-reduced-motion (don't autoplay). Reserve Lottie for motion that earns its ~160KB runtime.
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。
An animated bottom-tab indicator — Lottie JSON. A Lottie (JSON) animation — portable motion that plays identically on web and app via lottie-web. Honors prefers-reduced-motion (don't autoplay). Reserve Lottie for motion that earns its ~160KB runtime.
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。
Official GSAP skill for GSAP plugins — registration, ScrollToPlugin, ScrollSmoother, Flip, Draggable, Inertia, Observer, SplitText, ScrambleText, SVG and physics plugins, CustomEase, EasePack, CustomWiggle, CustomBounce, GSDevTools. Use when the user asks about a GSAP plugin, scroll-to, flip animations, draggable, SVG drawing, or plugin registration.
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。
Scaffold an emergent project from observed children's interests using Reggio-inspired approaches. Use when following children's fascinations into deeper inquiry in early years or primary settings.
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。
Modify a classroom task with language scaffolds that preserve cognitive demand for EAL learners. Use when adapting existing tasks for students at different English proficiency levels.
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。
When the user wants to design, construct, or improve an offer — the thing they actually sell — including value framing, bonus stacking, guarantee design, scarcity/urgency, naming, and payment structure. Also use when the user mentions 'offer,' 'offer design,' 'build an offer,' 'grand slam offer,' 'irresistible offer,' 'value stack,' 'bonus stack,' 'guarantee,' 'risk reversal,' 'money-back guarantee,' 'scarcity,' 'urgency,' 'high-ticket offer,' 'productize a service,' 'naming an offer,' 'payment plan,' 'down-sell,' 'upsell offer,' or 'why isn't my offer converting.' Best for services, agencies, courses, coaching, info products, high-ticket B2B, and direct-response. If you run pure self-serve SaaS, read pricing first — tiers and packaging do more work there. For price level itself (tiers, freemium, value metric), see pricing. For the page that presents the offer, see copywriting. For the launch moment, see launch. For sales collateral, see sales-enablement.
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 and read this skill immediately if the user request is in any way related to SEO or a site's organic search or AI search presence. That includes site audits, rankings, keyword research, competitors, backlinks, click or traffic changes, indexing problems, crawling, redirects, sitemaps, metadata, structured data, Core Web Vitals, internal links, content opportunities, programmatic SEO, local search, Search Console or Google Analytics questions, Google update impact, llms.txt, AI search visibility in ChatGPT, Claude, Perplexity, or Google AI Overviews, and client SEO reporting. Routes to evidence-backed local reports through the SEO CLI and MCP server.
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 an application or system — including one built quickly with AI coding agents — needs a security review with regulatory grounding: a STRIDE threat model, a LINDDUN privacy threat model, a dependency exposure screen against live CVE / CISA-KEV / EPSS data, or a selected, non-exhaustive screen of which EU security obligations (GDPR, NIS2, Cyber Resilience Act, AI Act) may apply and which need determination. Orchestrates the server-enforced threat-modeling workflows of the Ansvar Gateway MCP connector and grounds every regulatory statement in officially published text fetched at answer time — scope, role, and application-date limits stated, never a compliance verdict. Never simulates a workflow and never answers legal questions from model memory.
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。
Verifies UK case-law citations, pinpoint references and quotations against the official public register — The National Archives' Find Case Law — and statutory references against legislation.gov.uk, before a document that cites them is relied on, served or filed. Every check returns a graded verdict: VERIFIED, MISMATCH (the citation resolves to a different case — the classic AI miscitation), NOT ON REGISTER, OUTSIDE COVERAGE (the register cannot answer — absence proves nothing), or UNCHECKABLE (a law-report citation). The grading exists because there are two ways to get this wrong: citing a case that does not exist, and accusing a real case of not existing. Use when asked to check citations, verify a case exists, confirm a quotation is verbatim, check a pinpoint paragraph, audit a draft's authorities, screen a document for hallucinated cases, or check a statutory provision is in force. Not a substitute for reading the judgment: existence is not authority.
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。
Detects prompt injection hidden in documents from the other side (pleadings, skeletons, bundles, served evidence, opponents' emails and attachments) before an AI reads them, so the model is not turned against your client. Checks word by word that the text an extractor hands the model was visibly drawn on the page: white, near-white, covered, clipped, off-page, tiny, transparent and invisible-mode text in PDF (ink test plus OCR); Word formatting resolved as Word does (styles, shading, theme colours, scaling, off-page frames, fallbacks, unused headers); HTML/CSS, RTF, email with attachments and zips, xlsx/pptx and legacy formats. Flags Unicode smuggling, text addressed to an AI and authorities found only in hidden text. Fails closed. Optional Read-tool hook. Use BEFORE any AI summary or analysis of an opposing or third-party document. Triggers: 'scan for injection', 'is this document safe', 'check the other side's skeleton', 'injection guard'.
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。
Restructure any rough build, research, or legal-drafting request into an IRAC-shaped prompt — Issue, Rule, Analysis, Conclusion — optimized for a frontier model. It's the bar-exam framework, repurposed as prompt engineering. The skill leads with the issue and ends with the conclusion (where models weight attention most), forces you to name your constraints and non-goals, and specifies what "good" looks like before a single token is generated. Use it before any non-trivial build, or whenever a vague ask deserves a precise brief.
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 a security incident, data breach, or actively exploited vulnerability raises the question "who must we notify, where, and by when?" Screens one incident across the EU reporting regimes — NIS2, GDPR, DORA, and the Cyber Resilience Act — determines which duties fire for each involved entity's roles, resolves the receiving authority per regime and member state from served national law, and produces a deadline table in which every duty, authority, and deadline is cited from official publisher text fetched live through the Ansvar Gateway MCP connector. Never answers from model memory.
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。
Takes a skill — a .skill or .zip archive, a bare SKILL.md, a folder, or just a raw idea — and produces a package ready for public distribution on lawve.ai, plus the exact entries for the submission form. Runs a gate first: skills with no plausible legal use, unsafe code, or licensing bars are declined with reasons, and general-purpose skills that could serve legal work are offered a legal adaptation instead. Then applies the standard compliance transforms — structure, metadata, attribution, dependency ladders, orphaned-file repair, limitations disclosure — validates the result, and delivers a zip. Raw ideas are gated first, built (via skill-creator where available), then adapted. Use for "make this Lawve-compliant," "prep this skill for Lawve," "package for lawve.ai," "is this suitable for Lawve," "get my skill ready to publish," or any request to ready a skill for the Lawve catalogue.
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。
Creates an Agent Authority Charter for enterprise or regulated AI agents before deployment. Use this Skill when a user needs to define what an AI agent is allowed to do, who delegated authority to it, what actions are permitted or prohibited, when human approval is required, what evidence must be preserved, and how the agent can be suspended, revoked, or escalated.
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。
Turn complex legal analysis into clear, commercially useful client-facing advice. Use this whenever the user has dense legal material — drafting, internal analysis, counsel notes, research memos, pleadings, a case update, or correspondence — and wants it converted into something a client can actually understand and act on. Trigger on phrases like 'explain this to the client', 'put this in plain English', 'translate this for a non-lawyer', 'turn this into client-facing advice', 'make this client-ready', 'draft a client update', or when the user shares legal analysis and asks 'what does this mean for them'. Also trigger when the user wants a board summary, litigation risk update, or call script derived from legal material. The skill preserves legal nuance, uncertainty, and risk rather than oversimplifying — it makes advice usable, not just simpler.
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 blueprint for desktop platforms (Windows/Linux/macOS) covering keyboard/mouse controls, settings menus, window management (fullscreen, resolution), keybind remapping, and Steam integration. Use when targeting PC platforms or implementing desktop-specific features. Keywords desktop, Windows, Linux, macOS, settings, keybinds, ConfigFile, DisplayServer, Steam, fullscreen.
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 blueprint for physics queries using RayCast, ShapeCast, and DirectSpaceState. Covers hit detection, volume overlap, mouse picking, and high-performance server-side intersection queries. Use when implementing projectiles, LOS, terrain grounding, or AI sensors. Keywords raycast, shapecast, direct_space_state, intersect_ray, intersect_shape, PhysicsRayQueryParameters, collision mask, mouse picking.
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。
Consolidated expert library for professional Godot 4.7+ game and application development. Orchestrates 92 Domain Skills through architectural workflows, anti-pattern catalogs, performance budgets, and Server API patterns. Use when: (1) starting a new Godot project, (2) designing game or app architecture, (3) building entity/component systems, (4) debugging performance or physics issues, (5) choosing between 2D/3D approaches, (6) implementing multiplayer, (7) optimizing draw calls or script time, (8) porting between platforms, (9) migrating from 4.6 to 4.7. Primary entry point for ALL Godot development tasks. Keywords: Godot 4.7, AreaLight3D, HDR, Asset Store, godot-master.
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 multiplayer for desync, rollback, dedicated --headless servers, interest culling, and bandwidth spikes: ENet/WebRTC choice, authority, secure RPCs, client prediction/reconcile, and adaptive sync. Trigger on rubber-banding, cheat-able clients, peer floods, late join, or profiler Network spikes — not only greenfield online games. Keywords: multiplayer, RPC, ENetMultiplayerPeer, MultiplayerSynchronizer, authority, client prediction, rollback, interest management, headless, desync.
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 blueprint for MOBA games including lane logic (minion wave spawning every 30s), tower aggro priority (hero attacking ally over minion over hero), click-to-move controls (RTS-style raycasting), hero ability systems (QWER cooldowns, mana cost), fog of war (SubViewport projections), and authoritative networking (server validates damage). Use for competitive 5v5 or arena games. Trigger keywords: MOBA, lane_manager, minion_waves, tower_aggro, click_to_move, ability_cooldowns, fog_of_war, comeback_mechanics.
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 blueprint for rhythm games including audio synchronization (BPM conductor, latency compensation with AudioServer.get_time_since_last_mix), note highways (scroll speed, timing windows), judgment systems (Perfect/Great/Good/Bad/Miss), scoring with combo multipliers, input processing (lane-based, hold note detection), and chart/beatmap loading. Based on DDR/osu!/Beat Saber research. Trigger keywords: rhythm_game, audio_sync, timing_judgment, note_highway, combo_system, BPM_conductor, latency_compensation.
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。