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概要と使いどころ
Marketing leadership advisor on brand strategy, demand generation, and marketing operations. Use when building a marketing strategy, planning demand-gen campaigns, designing lead scoring models, or aligning marketing with revenue.
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。
Data leadership advisor on data strategy, governance, quality, and platform decisions. Use when defining a data strategy, scoring data maturity, auditing data governance, evaluating a data platform, or designing the data org.
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。
Meta-framework for how a company runs -- the connective tissue between C-suite roles (EOS, Scaling Up, OKR-native). Use when setting up company operations, selecting a management framework, designing meeting rhythms, or implementing OKRs.
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。
Customer leadership advisor on CX strategy, retention and expansion, and voice-of-customer programs. Use when defining a CX strategy, scoring CX maturity, planning churn interventions, or designing a VoC program.
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。
Playbook for designing SaaS and startup products that convert, retain, and monetize — landing pages & CRO, checkout & forms, onboarding/activation, churn reduction, pricing psychology, dashboards, behavioral-science tactics, feature discipline, positioning/ICP, go-to-market, and AI-era differentiation. Use when advising on product design, UX, conversion, landing pages, checkout, onboarding, trials, pricing, retention/churn, growth, or positioning for a startup or SaaS. Distilled from product designer Richard (@richardrx). Not for use on gambling, betting, or casino products.
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 the user has evaluation principles or a dataset but needs help choosing the right graders, designing evaluation metrics, creating LLM-as-judge prompts, combining multiple metrics into a composite score, or building an automated evaluation pipeline. Also use when the user mentions grader selection, metric design, judge prompt engineering, rubric design, evaluation pipeline code, or "how to evaluate [X] automatically." Outputs executable OpenJudge pipeline code.
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。
Stakeholder mapping, communication plan design, reporting hierarchy, and mid-matter comms updates. Use when setting up a new matter and needing to identify who needs what information, designing the communication rhythm, building reporting structures for multi-jurisdiction programmes, or updating the comms plan when the stakeholder landscape changes. Trigger on: 'stakeholder map', 'who needs to be kept informed', 'communication plan', 'reporting structure', 'who do we report to', 'how often do we meet', 'client wants more updates', 'new contact on the client side', 'build the comms plan', 'reporting hierarchy', 'HQ vs regions', 'who is the decision maker', 'comms rhythm', 'meeting cadence', 'status call schedule'.
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。
End-to-end external local counsel lifecycle management for multi-jurisdiction legal matters. LC selection criteria and capability assessment, engagement setup and instruction design, performance monitoring and check-in cadence, scope enforcement, and relationship escalation. Use when selecting local counsel for a jurisdiction, designing LC instructions, managing the LC check-in rhythm, enforcing scope boundaries when LC signals overreach, or escalating a performance or relationship issue beyond the matter team. Trigger on: 'which LC should we use', 'LC instruction', 'brief the local counsel', 'LC hasn't responded', 'LC is going off scope', 'LC scope dispute', 'confirm scope with LC', 'LC check-in', 'LC is slow', 'monitor the LC network', 'LC engagement letter', 'LC selection', 'what should we tell the local counsel', 'LC onboarding', 'LC performance issue', 'LC relationship problem'.
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。
Collaboration platform configuration methodology for legal matter sites. Site architecture, workflow identification, dashboard design, data quality governance, and user adoption for SharePoint, Teams, and equivalent platforms. M365 is the reference implementation — outputs are platform-agnostic enough to brief IT or build simple automations without becoming a Power Automate manual. Use when setting up a matter site, identifying workflows to automate, designing reporting dashboards, managing platform data quality, or driving user adoption. Trigger on: 'set up the matter site', 'configure SharePoint', 'build a dashboard', 'what should we automate', 'brief IT on this workflow', 'nobody is using the platform', 'data quality is poor', 'set up Teams channel', 'matter site structure', 'alerts and notifications', 'user training', 'platform governance', 'status dashboard', 'what workflows can we automate', 'matter site template'.
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。
Anchor a multidisciplinary unit in a real-world phenomenon that requires multiple subject lenses to understand. Use when designing integrated or phenomenon-based units across disciplines.
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。
Script a multi-turn tutoring dialogue with branching responses for anticipated student difficulties. Use when designing AI tutors, chatbot interactions, or structured one-to-one support scripts.
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。
Map which elements of an assignment benefit from AI assistance vs. which AI use undermines. Use when redesigning tasks for AI-age classrooms or setting defensible AI use policies for specific assignments.
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。
Map the epistemic structure of a subject to determine knowledge types and inform curriculum sequencing. Use when designing courses, restructuring programmes, or analysing knowledge architecture.
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。
Plan a unit using backwards design from desired outcomes through assessment evidence to learning activities. Use when starting a new unit or redesigning an existing one from standards.
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 a learning progression showing prerequisite-to-mastery steps for a target skill or understanding. Use when sequencing content, designing diagnostics, or mapping prerequisite gaps.
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。
Map knowledge components and skill hierarchies for a cognitive tutoring system or adaptive learning platform. Use when designing intelligent tutoring software or skill-based mastery systems.
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 cascading hint sequence for a problem type, revealing progressively without giving answers. Use when designing tutoring dialogues or scaffolded worksheets.
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。
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 patterns for adding multiplayer to single-player games including client-server architecture, authoritative server design, MultiplayerSynchronizer, lag compensation (client prediction, server reconciliation), input buffering, and anti-cheat measures. Use when retrofitting multiplayer, porting to online play, or designing networked gameplay. Trigger keywords: MultiplayerPeer, ENetMultiplayerPeer, SceneMultiplayer, MultiplayerSynchronizer, rpc, rpc_id, multiplayer_authority, client_prediction, server_reconciliation, lag_compensation, rollback.
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 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 patterns for adding multiplayer to single-player games including client-server architecture, authoritative server design, MultiplayerSynchronizer, lag compensation (client prediction, server reconciliation), input buffering, and anti-cheat measures. Use when retrofitting multiplayer, porting to online play, or designing networked gameplay. Trigger keywords: MultiplayerPeer, ENetMultiplayerPeer, SceneMultiplayer, MultiplayerSynchronizer, rpc, rpc_id, multiplayer_authority, client_prediction, server_reconciliation, lag_compensation, rollback.
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 designing scene tree structure — composition vs inheritance, when to split scenes, node hierarchy 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。