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Found 219 Skills
Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory Use when: conversation memory, remember, memory persistence, long-term memory, chat history.
Use when implementing agent memory, persisting state across sessions, building knowledge graphs, tracking entities, or asking about "agent memory", "knowledge graph", "entity memory", "vector stores", "temporal knowledge", "cross-session persistence"
Plan and build comprehensive Playwright E2E test suites with Page Object Model, authentication state persistence, custom fixtures, visual regression, and CI integration. Uses interview-driven planning to clarify critical user flows, auth strategy, test data approach, and parallelization before writing any tests.
Implement SQLite database patterns using the database.py interface with complete SQL isolation. MANDATORY for all database projects. Use when working with databases, data persistence, or SQLite.
Document solved problems for knowledge persistence
Choose and implement effector-storage persistence patterns for Effector apps. Use when tasks involve persist/createPersist usage, selecting adapters (local/session/query/broadcast/storage/asyncStorage/memory/nil/log), configuring clock/pickup/context/keyPrefix, validating data with contracts, handling done/fail/finally flows, SSR-safe adapter fallback with either, or debugging sync and serialization issues.
Create, read, and manage Feishu tasks with automatic user authorization. Use when you need to create tasks that your user can directly edit, read task lists, manage task details, or check calendar events. Supports automatic token refresh and persistence across sessions. All operations are performed with user identity, ensuring proper permissions.
Best practices for using agent-browser with Kernel cloud browsers. Use when automating websites with agent-browser -p kernel, dealing with bot detection, iframes, login persistence, or needing to find Kernel browser session IDs and live view URLs.
Implement, review, or improve data persistence using SwiftData. Use when defining @Model classes with @Attribute, @Relationship, @Transient, @Unique, or @Index; when querying with @Query, #Predicate, FetchDescriptor, or SortDescriptor; when configuring ModelContainer and ModelContext for SwiftUI or background work with @ModelActor; when planning schema migrations with VersionedSchema and SchemaMigrationPlan; when setting up CloudKit sync with ModelConfiguration; or when coexisting with or migrating from Core Data.
Command governance and automation playbook for weapp-ide-cli, including official CLI passthrough, automator commands, config/i18n persistence, command catalog export, and integration contracts with weapp-vite CLI dispatch.
Implements the Syncfusion WPF DockingManager control for Visual Studio-like docking interfaces with MDI/TDI support, floating windows, and auto-hide panels. Use this when creating docking layouts, window management systems, tabbed document interfaces, or IDE-style layouts in WPF applications. Covers dock panels, floating windows, auto-hide functionality, state persistence, and window management.
This skill should be used when users want to run any workload on Hugging Face Jobs infrastructure. Covers UV scripts, Docker-based jobs, hardware selection, cost estimation, authentication with tokens, secrets management, timeout configuration, and result persistence. Designed for general-purpose compute workloads including data processing, inference, experiments, batch jobs, and any Python-based tasks. Should be invoked for tasks involving cloud compute, GPU workloads, or when users mention running jobs on Hugging Face infrastructure without local setup.