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概要と使いどころ
Use when video content needs to be extracted as text: pasted YouTube links or IDs, requests to transcribe, summarize, quote, translate, convert video to text, or extract information from video content. Also use when a user shares a video URL without explanation and wants to know what it says. Not for uploads or account management.
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 YouTube is or could be relevant — even if not mentioned: pasted video/channel/playlist links, video IDs, @handles, creator lookups, video summaries, quotes, translations, topic research, tutorials, talks, lectures, expert discussions, product reviews, how-to guides, new product announcements, or anything where video content is fresher or richer than text search. Covers transcripts, video/channel search, channel browsing, playlists, and within-channel search. Not for uploads, account management, or written-source-only research.
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 YouTube data is needed without Google API quotas or OAuth setup: transcripts, video metadata, channel info, search results, playlists. Triggers on pasted YouTube links, creator names, @handles, topic research, video summaries, channel browsing, or any request where YouTube content would help — even if not mentioned explicitly. Not for uploads, account management, or written-source-only research.
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 YouTube is or could be relevant — even if not mentioned: pasted video/channel/playlist links, video IDs, @handles, creator lookups, video summaries, quotes, translations, topic research, tutorials, talks, lectures, expert discussions, product reviews, how-to guides, new product announcements, first looks, or anything where video content is fresher or richer than text search. Covers transcripts, video/channel search, channel browsing, playlists, and within-channel search. Not for uploads, account management, or written-source-only research.
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 creating a ChatGPT pet or Codex pet with Scenario: hatching an animated companion from a text idea, a character, mascot or brand cue, or reference photos and art; making the 1536x2288 v2 pet sprite sheet with nine animation states and sixteen look directions, the 1536x1872 v1 sheet ChatGPT web uploads, a pixel-perfect pixel-art pet, an animated GIF of the pet, or a Codex pet.json package.
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 building a Unity 6.3 level or open world: terrain from code or heightmaps, procedural islands, erosion, splat and foliage rules, trees and grass, ProBuilder graybox, level gym, modular kit and prefab placement, set dressing, landmarks and player guidance, the island's edge, spline roads, WFC, fog, additive scene streaming, or a world that hitches, pops in, leaks memory or runs slow on mobile. Keywords: Terrain, TerrainData, ProBuilder, blockout, graybox, modular kit, NavMesh, LoadSceneAsync, open world.
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 structuring Godot 4.7 game code: folders, scenes and nodes, signals or an event bus autoload, custom Resources for item data, components (health, hitbox, hurtbox), an inventory, save and load, InputMap and key rebinding for keyboard, mouse and gamepad, GDScript static typing and style, or GDScript vs C#; or when code is spaghetti, a folder scan breaks in the export, a save loads wrong, the gamepad does nothing, or @onready is null.
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。
Debug Kubernetes pods, nodes, and workloads. Use when pods are failing, containers crash, nodes are unhealthy, or users mention debugging, troubleshooting, or diagnosing Kubernetes issues.
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。
Kubernetes backup and restore with Velero. Use when creating backups, restoring applications, managing disaster recovery, or migrating workloads between clusters.
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。
Deploy and manage Kubernetes workloads with progressive delivery. Use for deployments, rollouts, blue-green, canary releases, scaling, and release management.
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。
Serverless cloud compute for running scientific workloads at scale
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。
Deploys and manages Kubernetes workloads with deployment manifests, pod security policies, RBAC, Helm charts, NetworkPolicies, and multi-cluster management.
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 asks to "analyze this codebase", "document this service", "generate technical docs", "I inherited this code", "help me understand this system", "create docs for this project", "what does this system look like", "onboard me to this codebase", "this codebase has no docs", "visualize the architecture from code", or any explicit request to produce structured documentation or architecture diagrams from an existing codebase. Specifically optimized for AWS workloads (CDK, CloudFormation, Terraform) with source-of-truth citations. Do NOT activate for code reviews, single-function explanations, generating new code, or general coding tasks.
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。
NIL (Name, Image, and Likeness) contract analysis for NCAA student-athletes from the athlete's perspective. Use when user says 'review this NIL contract', 'analyze this NIL deal', 'check this athlete agreement', 'review my NIL agreement', or uploads a PDF NIL contract for review. Identifies red flags, missing protections, and compliance issues. Produces a structured review memorandum with negotiation positions. Do NOT use for general contract review, employment agreements, non-NIL endorsements, or brand-side deal analysis.
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 this skill whenever a lawyer or mediator needs help analyzing a dispute for mediation purposes. This includes: reviewing case materials (pleadings, contracts, correspondence, evidence) to identify issues in dispute, summarizing each party's position and interests, conducting legal analysis of the key issues, proposing mediation strategies or settlement directions, and preparing for mediation sessions. Trigger this skill when the user mentions 'mediation', 'dispute analysis', 'settlement', 'dispute resolution', 'identify issues in dispute', 'party positions', 'mediation brief', 'case analysis for mediation', 'ADR', 'mediation preparation', 'caucus strategy', 'settlement options', or any request to analyze a conflict between two or more parties with the goal of finding resolution. Also trigger when the user uploads case files and asks for a structured breakdown of who wants what, what the core disagreements are, or how the case might settle. Even if the user doesn't explicitly say 'mediation', trigger when the context involves analyzing opposing positions in a dispute with a resolution-oriented (rather than litigation-oriented) goal.
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。
Calendar litigation and arbitration deadlines from a scheduling order. Parses a PDF scheduling order, identifies key dates, computes backward deadlines using the applicable rules (Colorado CRCP, Federal FRCP, or arbitration forum rules for AAA/JAMS), and generates an .ics calendar file for Outlook or Google Calendar import. Use this skill whenever the user mentions: litigation deadlines, scheduling order, case management order, deadline calendaring, discovery deadlines, trial preparation deadlines, arbitration scheduling, or anything related to computing or tracking court or arbitration deadlines. Also trigger when the user uploads a PDF that appears to be a court scheduling order or arbitration scheduling order.
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 any OFAC or OFSI enforcement action — by URL, pasted text, or uploaded document — and produce a structured root cause analysis as a formatted Excel (.xlsx) spreadsheet. Use this skill whenever a user names, links to, pastes, or uploads an OFAC or OFSI enforcement action and asks for any of the following: root cause analysis, compliance gaps, what went wrong, lessons learned, organizational self-assessment, or remediation planning. Also trigger when a user asks "analyze this enforcement action", "what were the root causes", "turn this into a checklist", or "how do I make sure this doesn't happen to us". Outputs a single-sheet .xlsx table with six columns: Root Cause | What Went Wrong | How It Went Wrong | What Could Have Stopped It | Is my organization immune to this? (Yes/No/Partial) | Notes.
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。
Complete prep for all three scored components of the California Bar Exam: the five written ESSAYS (13 subjects — Business Associations, Civil Procedure, Community Property, Constitutional Law, Contracts, Criminal Law & Procedure, Evidence, Professional Responsibility, Real Property, Remedies, Torts, Trusts, Wills & Succession), the PERFORMANCE TEST, and the multiple-choice MBE (7 subjects). Trigger whenever someone is studying for the California bar (or the MBE) and says things like: "give me the rule for [issue]", "big issues in [subject]", "drill/quiz me on [topic]", "MBE questions on [subject]", "teach me [doctrine]", "build an attack outline", "grade my essay", "memorizable paragraph for [issue]", "performance test approach", or "make a study plan" — or names any tested essay/MBE subject in a study, memorization, drilling, or practice-question context. Also trigger when a student uploads a practice essay, PT, or question set to be graded or turned into rule blocks. When in doubt during bar prep, trigger.
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。
Rise + fade key elements in as the page loads, optionally staggered. Use for hero content and a small group of important elements. Honors prefers-reduced-motion. For long lists or off-screen content use scroll-reveal instead; never delay must-read content by more than a moment.
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。
Skeleton placeholders with a soft sweeping shimmer while content loads. Use to fill space for cards/lists/profiles that are still loading and make the wait feel shorter. Honors prefers-reduced-motion (static skeleton). Only show while real content is loading — never as decoration.
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。
Agentic eyes for Godot work: cross-platform screenshot CLI (asset/region/window/screen) to budgeted WebP, TEMP editor viewport bridge under .gdskills/, and Taste Receptor Atlas v2 (~237 micro-receptors × 0–2: hierarchy, contrast, typography×41, affordance, space, color, icon, composition, light/FX, motion-tells, anti-slop, originality, identity). Use when agents must see UI, assets, or the editor — not for in-game screenshot Autoloads. Keywords: agent vision, screenshot, WebP, visual QA, taste receptors, typography, UI review, asset sheet, editor viewport, anti-slop.
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。
Agentic eyes for Godot work: cross-platform screenshot CLI (asset/region/window/screen) to budgeted WebP, TEMP editor viewport bridge under .gdskills/, and Taste Receptor Atlas v2 (~237 micro-receptors × 0–2: hierarchy, contrast, typography×41, affordance, space, color, icon, composition, light/FX, motion-tells, anti-slop, originality, identity). Use when agents must see UI, assets, or the editor — not for in-game screenshot Autoloads. Keywords: agent vision, screenshot, WebP, visual QA, taste receptors, typography, UI review, asset sheet, editor viewport, anti-slop.
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。
Strix 文件上传安全测试手册,覆盖扩展名绕过、Content-Type 操控与路径穿越;触发名:strix-insecure-file-uploads
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 managing dependencies between systems — autoloads, service locators, @export injection, and scene injection patterns
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。