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Found 67 Skills
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Game server architecture, scalability, matchmaking, and backend systems for online games. Build robust, scalable multiplayer infrastructure.
Shared domain models for Revet libraries - Metadata, Identifier, SchemaValidation
Load this skill immediately when the user expresses any intent. System capabilities (tools/knowledge/scripts) live inside the plugin and are maintained through plugin updates. User data must live at project-level `.claude/pensieve/` and is never overwritten by the plugin. When the user asks to improve Pensieve system behavior (plugin content), you must use the Self-Improve tool (`tools/self-improve/_self-improve.md`).
Provides comprehensive guidance for Avue CRUD component including table operations, form handling, and data management. Use when the user asks about Avue CRUD, needs to implement table CRUD operations, or build data management interfaces.
Universal Strava API integration for fitness data management. Use when working with Strava activities, athlete profiles, segments, routes, clubs, or any fitness tracking data. Triggers on requests to get/create/update activities, analyze training stats, export routes, explore segments, or interact with Strava data programmatically.
End-to-end testing patterns with Playwright for full-stack Python/React applications. Use when writing E2E tests for complete user workflows (login, CRUD, navigation), critical path regression tests, or cross-browser validation. Covers test structure, page object model, selector strategy (data-testid > role > label), wait strategies, auth state reuse, test data management, and CI integration. Does NOT cover unit tests or component tests (use pytest-patterns or react-testing-patterns).
A Pythonic interface to the HDF5 binary data format. It allows you to store huge amounts of numerical data and easily manipulate that data from NumPy. Features a hierarchical structure similar to a file system. Use for storing datasets larger than RAM, organizing complex scientific data hierarchically, storing numerical arrays with high-speed random access, keeping metadata attached to data, sharing data between languages, and reading/writing large datasets in chunks.
Strategic guidance for choosing and implementing testing approaches across the test pyramid. Use when building comprehensive test suites that balance unit, integration, E2E, and contract testing for optimal speed and confidence. Covers multi-language patterns (TypeScript, Python, Go, Rust) and modern best practices including property-based testing, test data management, and CI/CD integration.
Reviews Phoenix LiveView code for lifecycle patterns, assigns/streams usage, components, and security. Use when reviewing LiveView modules, .heex templates, or LiveComponents.
Use to define schemas, topic tags, and lineage metadata for enriched signals.
React Native & Expo engineering standards.