Loading...
Loading...
Found 219 Skills
Integrate OnboardJS into React projects for building user onboarding flows. Use when: (1) Setting up OnboardJS in a React/Next.js project (2) Creating multi-step onboarding, wizards, or guided flows (3) Implementing conditional navigation, data persistence, or step validation (4) Working with OnboardingProvider, useOnboarding hook, or step components Triggers: "onboarding", "onboardjs", "wizard flow", "user onboarding", "guided tour", "multi-step form"
Analyze Windows Registry hives for forensic investigation. Use when investigating malware persistence, user activity, system configuration changes, or evidence of program execution. Supports offline registry analysis from disk images or extracted hives.
Execute complex tasks with intelligent workflow management and cross-session persistence. Use when managing large projects, tracking progress across sessions, or orchestrating multi-phase work.
Build Python agents with Agentica SDK - @agentic decorator, spawn(), persistence, MCP integration
Apache Pekko + Scala 3によるCQRS/Event Sourcing実装ガイド。 PersistenceEffectorを用いた集約アクター、ドメインモデルとアクターの分離、 状態遷移の型安全な表現、イベント設計、Protocol Buffersシリアライズ、 ZIOベースのユースケース層、リードモデルアップデータの実装パターンを提供する。 対象言語: Scala 3限定。CQRS/Event Sourcingアーキテクチャが前提の場合のみ使用。 トリガー条件: 「Scala」かつ「CQRS」または「Event Sourcing」または「Pekko」が リクエストに含まれる場合のみ起動。Scala以外の言語やCQRS/ES以外のアーキテクチャでは このスキルを使用してはならない。 トリガー：「PekkoでCQRS/ESを実装したい」「Scalaで集約アクターを書きたい」 「PersistenceEffectorの使い方」「Pekkoのイベントソーシング」 「ScalaでCQRSのコマンド側を実装」「Pekkoで状態遷移を管理」 といったPekko + Scala + CQRS/ES実装リクエストで起動。 非トリガー：「CQRSのトレードオフ」「イベントソーシングとは」「JavaでCQRS」 「GoでEvent Sourcing」「CQRSの概念を教えて」など、Scala/Pekko以外や概念的な質問では 起動してはならない。
Autonomous AI Project Agent & Cron Task Runner. Orchestrates repetitive AI-driven engineering tasks with state persistence (Memory) and advanced workflow controls.
Analyze codebases from the bottom up and generate a hierarchical README.md document tree. Start analysis from leaf directories, generate README.md files for each directory containing one-sentence descriptions of files, classes, and functions, and summarize layer by layer upwards to form a complete codebase documentation system. Supports state persistence and resumable analysis, suitable for scenarios such as understanding new projects, generating technical documentation, and analyzing code structures. Use this skill when you need to understand codebase structures, analyze function implementations, or generate code documentation.
Persist canister state across upgrades. Covers StableBTreeMap and MemoryManager in Rust, persistent actor in Motoko, and upgrade hook patterns. Use when dealing with canister upgrades, data persistence, data lost after upgrade, stable storage, StableBTreeMap, pre_upgrade traps, or heap vs stable memory. Do NOT use for inter-canister calls or access control — use multi-canister or canister-security instead.
Motoko language pitfalls and modern syntax for the Internet Computer. Covers persistent actor requirements, stable types, mo:core standard library, type system rules, and common compilation errors. Use when writing Motoko canister code, fixing Motoko compiler errors, or generating Motoko actors. Do NOT use for deployment, icp.yaml config, or CLI commands — use icp-cli instead. Do NOT use for upgrade persistence patterns — use stable-memory instead.
Implement the CommandBar control in Windows Forms to create customizable toolbars, rebars, and status bars with docking, floating, and state persistence capabilities. The CommandBar provides Office-like UI organization with support for hosting multiple controls, user layout customization, and serializable state management.
Guides implementation of agent memory systems, compares production frameworks (Mem0, Zep/Graphiti, Letta, LangMem, Cognee), and designs persistence architectures for cross-session knowledge retention. Use when the user asks to "implement agent memory", "persist state across sessions", "build knowledge graph for agents", "track entities over time", "add long-term memory", "choose a memory framework", or mentions temporal knowledge graphs, vector stores, entity memory, adaptive memory, dynamic memory, or memory benchmarks (LoCoMo, LongMemEval). A core context engineering skill — also activates when the user mentions "context engineering" or "context-engineering" in the context of durable agent knowledge and cross-session persistence.
Unity New Input System correctness patterns. Catches common mistakes with action reading (triggered vs IsPressed vs WasPressedThisFrame), action map switching, rebinding persistence, InputValue lifetime, PassThrough vs Value, local multiplayer device assignment, and control scheme auto-switching. PATTERN format: WHEN/WRONG/RIGHT/GOTCHA. Based on Unity 6.3 LTS.