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概要と使いどころ
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。
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。
When the user wants to optimize signup, registration, account creation, or trial activation flows. Also use when the user mentions "signup conversions," "registration friction," "signup form optimization," "free trial signup," "reduce signup dropoff," "account creation flow," "people aren't signing up," "signup abandonment," "trial conversion rate," "nobody completes registration," "too many steps to sign up," or "simplify our signup." Use this whenever the user has a signup or registration flow that isn't performing. For post-signup onboarding, see onboarding. For lead capture forms (not account creation), see cro.
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 optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," "new user experience," "users aren't activating," "nobody completes setup," "low activation rate," "users sign up but don't use the product," "time to value," or "first session experience." Use this whenever users are signing up but not sticking around. For signup/registration optimization, see signup. For ongoing email sequences, see emails.
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。
Guides stable API and interface design. Use when designing APIs, module boundaries, or any public interface. Use when creating REST or GraphQL endpoints, defining type contracts between modules, or establishing boundaries between frontend and backend.
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。
Translate a confirmed mini-program product specification or bounded feature into an implementable architecture covering modules, pages, components, services, canonical state sources, data models, interfaces, permissions, failures, caching, concurrency, idempotency, migration, rollback, external dependencies, and architecture decision records. Use when users ask how to structure a mini program, design data or APIs, divide frontend and cloud responsibilities, evolve an existing system safely, or prepare implementation after product semantics are stable. Preserves product meaning, current repository constraints, user-owned changes, and verifiable acceptance behavior rather than redesigning the product for technical convenience.
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 one-page HTML/PDF resumes from copy-paste YAML using one of 12 official templates. HARD GATES: deliver exactly one A4 page; never invent a layout — copy assets/templates/<id> into output/<id>/ and edit that copy only. Keep a full inventory in raw.data.yaml. For each job, COPY selected entries into resume.data.yaml (polish there), then apply that file to a template. Apply pasted YAML by replacing visible text in the official resume.html, then run QA. Default template is basic-a4. Use when creating, iterating, polishing copy, migrating, exporting, or designing resume/CV HTML/PDF. For polishing resume copy, prefer writing-oriented models (Claude Fable 5 / Claude Opus 4.6-4.7 or Opus 5 / Kimi K3 / GLM-5.1-5.3-max / Qwen 3.8 Max); do not use GPT-5.6 Terra/Luna or GPT-5.5 Instant.
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 interpreting research findings, evaluating scientific evidence, analyzing mechanisms, comparing competing hypotheses, designing experiments, or constructing scientific arguments.
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 interpreting biological research findings, evaluating life science evidence, analyzing molecular or cellular mechanisms, comparing competing biological hypotheses, designing or critiquing experiments in biology, genetics, genomics, cell biology, immunology, neuroscience, ecology, or any life science domain. Triggers on questions about gene function, pathways, phenotypes, GWAS hits, single-cell data, animal models, clinical translation, evolutionary arguments, or any biology/life science reasoning task.
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, reviewing, or refactoring a CLI that must serve AI agents alongside humans, or when converting an API or SDK into an agent-usable CLI interface.
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 measure Developer Relations programs across documentation, community, technical content, integrations, events and developer advocacy. Use when designing DevRel strategy, improving developer activation, launching an API/SDK, evaluating sponsorships, or connecting community activity to product adoption and 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。
Build and grow developer and user communities from scratch — covering ambassador programs, community-led growth (CLG), event operations, content strategy, and health metrics. Grounded in real playbooks from Notion, Lovable, AFFiNE, ClickUp, Asana, and Lark. Use when: building a community for an open-source project, SaaS product, or brand; recruiting and managing ambassadors or community leaders; planning community events (online/offline meetups, AMAs, hackathons); designing ambassador tier/points systems; setting community health KPIs; launching a Build-in-Public strategy; setting up Discord, Slack, or Lark communities; running developer relations (DevRel); or when the user asks about community operations, ambassador programs, CLG, user advocacy, KOC/KOL cultivation, UGC flywheels, community monetization, or any variation of "how do I grow my community".
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。
Craft CMS 5 content modeling — sections, entry types, fields, Matrix, relations, project config, and content architecture strategy. Covers choosing section types, designing entry types and field layouts, selecting field types, configuring Matrix and nested entries, relations and eager loading, and multi-site propagation.
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。
Architectural guidance for building node-based UIs with React Flow. Use when designing flow-based applications, making decisions about state management, integration patterns, or evaluating whether React Flow fits a use case.
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。
Go application architecture with net/http 1.22+ routing, project structure patterns, graceful shutdown, and dependency injection. Use when building Go web servers, designing project layout, or structuring application dependencies.
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 persistence patterns in Go covering raw SQL with sqlx/pgx, ORMs like Ent and GORM, connection pooling, migrations with golang-migrate, and transaction management. Use when implementing database access, designing repositories, or managing schema migrations.
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。
Guides architectural decisions for LangGraph applications. Use when deciding between LangGraph vs alternatives, choosing state management strategies, designing multi-agent systems, or selecting persistence and streaming approaches.
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。
Guides architectural decisions for Deep Agents applications. Use when deciding between Deep Agents vs alternatives, choosing backend strategies, designing subagent systems, or selecting middleware approaches.
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。
Create Agent Skills with best practices, structure, validation, and testing. Use when designing or refining skills, prompts, references, or supporting files.
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。
Reserved-field rules and field-number lookup for evolving AppSettings, plus the Rust/Kotlin diagnostics wire contract. Use before assigning or removing a proto field. DataStore mapping: protobuf-datastore.
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。
Explicit request only -- never invoke implicitly, never expose signing secrets. Prepares and publishes one exact-SHA RIPDPI release via the release contract. Use when asked to prepare or publish a version.
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 or implementing Spring Data JPA on Spring Boot 4 — repository boundaries, projections, query patterns, custom repositories, CQRS read models, entity relationships, or persistence performance fixes. Not for generic SQL help, database admin work, or project-wide migration (see the springboot-migration skill).
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 applications with Univer Office SDK, covering the Web SDK (browser Office editors, headless Sheets and Docs in Node), Server SDK (self-hosted OT collaboration, storage, auth, Office import/export), AI SDK (agent-operated Office CLIs, reviewable Worktrees), and Binding SDK (plain HTML pages bound to live Sheet data). Use when starting or designing any Univer-based app or choosing Univer packages, including when the user describes a spreadsheet, document, collaboration, or AI-office need without naming a Univer 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。