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概要と使いどころ
Jira expert for project setup, workflow design, JQL queries, custom fields, automation rules, dashboards, and reporting. Use for Jira configuration, advanced search, board and dashboard creation, and technical Jira operations.
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。
SEO covering technical SEO, content optimization, link building, keyword research, and search analytics. Use when auditing technical SEO, researching keywords, optimizing on-page elements, or analyzing organic search performance.
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。
App Store Optimization toolkit for researching keywords, optimizing metadata, and tracking mobile app performance on Apple App Store and Google Play Store.
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。
Design observability strategies: SLI/SLO frameworks, alerting, and dashboards. Use when instrumenting a production service, tuning alert rules, designing Grafana dashboards, defining SLOs and error budgets, or reducing alert fatigue.
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。
Business intelligence across dashboard design, visualization, and reporting automation. Use when designing dashboards, building KPI frameworks, automating reports, creating data stories, or optimizing BI tool performance.
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。
Systematic competitor tracking that feeds positioning, battlecards, and roadmap decisions. Use when analyzing competitors, building battlecards, tracking market moves, conducting win/loss analysis, or updating positioning.
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 new AI names or unstructured AI market signals into a keyword priority table. For each name it finds the generic search terms downstream of it, screens them for relevance, and checks novelty, demand size and momentum against Google Ads volume and Google Trends, ending in prioritize, watch or skip. Use when the user has new model, product or repository names (or an AI listening report, a batch of posts, a changelog) and asks which keywords to build pages or tools for. Runs the new-term-radar command line; needs an AISA_API_KEY, and a GOANYAPI_API_KEY improves it.
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。
Cluster keywords into pillar and spoke pages by SERP overlap via script. "cluster these keywords"
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。
Research keywords via the connected data source: intent, gaps. Grouping → keyword-cluster. "what keywords should we target"
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。
Verification-first methodology for the post-WWII tribunals: the IMT at Nuremberg, the twelve Nuremberg Military Tribunals, and the IMTFE at Tokyo. Citations are verified against the official records (Blue/Green Series, Pritchard-Zaide) and the digital archives (Avalon, Harvard NTP, UVA IMTFE). Guards the four classic traps (IMT vs NMT; Nuremberg vs Tokyo; Charter article numbers; majority judgment vs separate opinions, e.g. the Pal dissent). Research aid, not legal advice. Part of the open-source "Skills for International Justice" library — methodology: github.com/jeannesulzer/international-criminal-tribunals-skills
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。
Compliant, retrieval-grounded research over investor-State dispute settlement (ISDS) awards and decisions. Use when the user asks about ICSID / investment-treaty arbitration cases, awards, or doctrines (fair and equitable treatment, expropriation, jurisdiction, costs, annulment, etc.) and wants answers grounded in the actual document text with pinpoint citations. Identifies the correct document on the case page, confirms it against the PDF's own first pages, retrieves primary documents on demand from ICSID, PCA, etc., never scrapes or hosts a corpus in violation of applicable terms, and cites only retrieved text.
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。
EU AI Act Knowledge Engine — authoritative regulatory Q&A grounded in 70 official EU source documents (including the 2026 Commission draft guidelines on Art. 6 high-risk classification — general principles, Annex I, Annex III). Answers any question about the AI Act with article-level citations from the full regulation text, Commission guidelines, EDPB/EDPS opinions, codes of practice, harmonised standards, FRIA guides, incident templates, and sector-specific guidance. This skill should be used when the user asks about the "EU AI Act", "AI Act regulation", "Regulation 2024/1689", "KI-Verordnung", asks to "explain an AI Act article", "what does Article X say", "AI Act requirements", "AI Act penalties", "AI Act timeline", "GPAI obligations", "high-risk AI", "prohibited AI practices", "AI Act and GDPR", "fundamental rights impact assessment", "AI Act standards", "AI Act national implementation", "AI literacy", "serious incident reporting", "Digital Omnibus", "AI regulatory sandbox", or any question about EU artificial intelligence regulation. Also triggers on German terms: "KI-Gesetz", "KI-Verordnung", "Hochrisiko-KI", "KI-Kompetenz", "Grundrechte-Folgenabschaetzung", "GPAI-Verhaltenskodex". For assessment workflows that produce a classification decision rather than a knowledge answer, offer to run a structured risk-tier classification in-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。
Words sit softly blurred; one snaps into focus at a time — leads the eye across a short phrase. One per view; short phrases. Under prefers-reduced-motion all words stay sharp.
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 stack of cards springs and fans into place on view — a lively hero for a small set (3–5). One set per view. Shown flat/instant under prefers-reduced-motion.
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。
Words cascade into place — a kinetic title. A bold, canvas-based effect from Open Design's html-ppt fx pack — for slides and launch videos. Guards prefers-reduced-motion (does not start). One per screen; on web use sparingly.
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。
Present project-design pathway options and orchestrate regenerative projects using backwards design, PBL, SEEDS, compassionate systems action, or civic/service pathways.
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。
Unpack a broad standard or competency descriptor into specific, assessable success criteria and sub-skills. Use when interpreting curriculum standards or writing learning objectives.
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 platformer games including precision movement (coyote time, jump buffering, variable jump height), game feel polish (squash/stretch, particle trails, camera shake), level design principles (difficulty curves, checkpoint placement), collectible systems (progression rewards), and accessibility options (assist mode, remappable controls). Based on Celeste/Hollow Knight design research. Trigger keywords: platformer, coyote_time, jump_buffer, game_feel, level_design, precision_movement.
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 architectural standards for building scalable Godot GAMES (RPGs, Platformers, Shooters) using the Composition pattern (Entity-Component). Use when designing player controllers, NPCs, enemies, weapons, or complex gameplay systems. Enforces "Has-A" relationships for game entities. Trigger keywords: Entity-Component, ECS, Gameplay, Actors, NPCs, Enemies, Weapons, Hitboxes, Game Loop, Level Design.
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 GDScript landmine guidance: static typing opcodes, signal-up/call-down, %UniqueName/@onready lifecycle, Callable bind/unbind, await sequences, typed collections, and safe Dictionary iteration. Use for code review, refactoring hot paths, or project standards. Trigger keywords: static_typing, signal_architecture, unique_nodes, @onready, class_name, signal_up_call_down, Callable.bind, typed_collections, await_sequence.
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 digital card games (CCG/Deckbuilders) including card data structures (Resource-based), deck management (draw/discard/reshuffle), turn logic, hand layout (arcing), drag-and-drop UI, effect resolution (Command pattern), and visual polish (godot-tweening, shaders). Use for CCG, deckbuilders, or tactical card games. Trigger keywords: card_game, deck_manager, card_data, hand_layout, drag_drop_cards, effect_resolution, command_pattern, draw_pile, discard_pile.
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 platformer games including precision movement (coyote time, jump buffering, variable jump height), game feel polish (squash/stretch, particle trails, camera shake), level design principles (difficulty curves, checkpoint placement), collectible systems (progression rewards), and accessibility options (assist mode, remappable controls). Based on Celeste/Hollow Knight design research. Trigger keywords: platformer, coyote_time, jump_buffer, game_feel, level_design, precision_movement.
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 architectural standards for building scalable Godot GAMES (RPGs, Platformers, Shooters) using the Composition pattern (Entity-Component). Use when designing player controllers, NPCs, enemies, weapons, or complex gameplay systems. Enforces "Has-A" relationships for game entities. Trigger keywords: Entity-Component, ECS, Gameplay, Actors, NPCs, Enemies, Weapons, Hitboxes, Game Loop, Level Design.
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 GDScript landmine guidance: static typing opcodes, signal-up/call-down, %UniqueName/@onready lifecycle, Callable bind/unbind, await sequences, typed collections, and safe Dictionary iteration. Use for code review, refactoring hot paths, or project standards. Trigger keywords: static_typing, signal_architecture, unique_nodes, @onready, class_name, signal_up_call_down, Callable.bind, typed_collections, await_sequence.
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。