182 件 ・ 関連度順
概要と使いどころ
Write, review, or improve SwiftUI code following best practices for state management, view composition, performance, macOS-specific APIs, and iOS 26+ Liquid Glass adoption. Use when building new SwiftUI features, refactoring existing views, reviewing code quality, or adopting modern SwiftUI 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。
Current attested Codex, Claude Code, and Agent Skills extension contracts for skilltap. Use when designing, implementing, reviewing, or documenting harness adapters; plugin or marketplace manifests; native plugin lifecycle; skill directories or SKILL.md frontmatter; AGENTS.md/CLAUDE.md bridges; configuration scopes; compatibility transfer; adoption, reconciliation, status, or update behavior.
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: 'intake this repo/skill', 'evaluate external skill', 'should we adopt X', a candidate repo URL plus an adoption question, or any external skill/workflow/tool surfaces as a possible fit for Agistra. Structured front-door evaluation of external skills, workflows, and similar capability artifacts before any install, promotion, or adaptation decision. Ends in exactly one classification: Install candidate, Adapt concept, or Reject. Never install first — intake first.
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。
Write, review, or improve SwiftUI code following best practices for state management, view composition, performance, macOS-specific APIs, and iOS 26+ Liquid Glass adoption. Use when building new SwiftUI features, refactoring existing views, reviewing code quality, or adopting modern SwiftUI 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。
「これから組織として生成 AI 導入を検討する委員会で何を議論すべきか」 「AI 利用ガイドライン策定の優先順位を決めたい」「執行部に上程する導入検討資料を作りたい」 「自学の AI 導入成熟度はどの段階か診断したい」「学長説明用 1 ページ要旨を作りたい」 場面で使う、大学組織としての AI 導入検討支援スキル。 3 カテゴリ × 2 ステップ × 2 主体のチェックリストと 5 段階成熟度モデルで合意形成を支援する。
Analyze Chronote product adoption with PostHog and Langfuse, including active users, meetings, feature usage, AI telemetry, and privacy-safe resolution of active Discord guild IDs to live server names.
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。
Manage change for AI adoption in organizations. TRIGGERS - Use when user needs help with ai-change-management related 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。
Build AI champion programs for adoption. TRIGGERS - Use when user needs help with ai-champion-program related 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。
Builds an interactive HTML dashboard visualizing the Agent Skills ecosystem by fetching live data from github.com/agentskills/agentskills. Use this skill whenever the user wants to explore, research, or visualize Skills architecture, the SKILL.md spec, ecosystem adoption, repo stats, or any Skills intelligence dashboard. Trigger when the user mentions "skills dashboard", "skills ecosystem", "skills architecture overview", "agentskills repo", or wants to analyze how different tools implement Agent Skills. Optimized for Perplexity Computer — Computer fetches all data live, no static files required.
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 scale partner ecosystems that drive revenue and platform adoption. Use when building partner programs from scratch, tiering partnerships, managing co-marketing, making build-vs-partner decisions, or structuring crawl-walk-run partner deployment.
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。
Four-phase framework for onboarding enterprise customers from contract to value realization. Use when implementing new enterprise customers, preventing churn during onboarding, or solving the adoption cliff that kills deals post-go-live. Includes the Week 4 ghosting pattern.
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。
Launch new products from idea to first customers. Use when launching products, finding early adopters, building launch week playbooks, diagnosing why adoption stalls, or learning that press coverage does not equal growth. Includes the three-layer diagnosis, the 2-week experiment cycle, and the launch that got 50K impressions and 12 signups.
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。
Implement an executable BDI agent cycle with events, context-guarded plans, intention stacks, selection functions, and belief revision. Use when designing or debugging AgentSpeak-style runtimes or concrete BDI program semantics. NOT for high-level BDI adoption, organizational modeling, norms, or hypertree team planning.
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。
Introduce people to AI, agentic AI, and AI skills with appropriate pedagogy for any audience. Covers LLM analogies, progressive complexity paths, aha-moment demos, audience-tailored explanations, workshop design, and overcoming emotional barriers to AI adoption. Activate on 'explain AI', 'introduce AI', 'AI workshop', 'AI demo', 'teach AI', 'AI literacy', 'onboard to AI', 'AI evangelism', 'explain agentic', 'explain skills to', 'AI training session', 'AI onboarding'. NOT for teaching ML engineering (use ai-engineer), not for building AI features (use ai-engineer), not for prompt engineering (use prompt-engineer), not for building training data pipelines.
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。