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Lessley
Lessley contains 10 collected skills from Lessley-Fin, with repository-level occupation coverage and site-owned skill detail pages.
Skills in this repository
Build the Lessley React frontend for production. Use when: preparing a deployment, checking that TypeScript compiles, or verifying the production bundle before shipping.
Start the Vite dev server for the Lessley React frontend. Use when: developing UI features, testing visual changes, debugging frontend behavior, or verifying that components render correctly.
Guide for creating new features in the Lessley React frontend. Use when: adding a new page, feature module, or API integration following the established architecture patterns.
Run ESLint on the Lessley React frontend. Use when: checking code quality, enforcing consistent patterns, or before committing frontend changes.
Run Vitest tests for the Lessley React frontend. Use when: verifying component behavior, testing hooks, checking auth store logic, validating route guards, or running the test suite before committing.
Run TypeScript type checking on the Lessley React frontend without emitting output. Use when: checking for type errors, validating refactors, or debugging import issues.
Explains and enforces the layered architecture used in Lessley services. Use when: reviewing or writing controllers, services, or repositories; deciding where new logic should live; or ensuring a controller does not contain business logic.
Test distributed systems across service boundaries. Use when: validating data contracts between Python/Node.js/C# services (Scraper ↔ Optimizer ↔ Personalization), testing MongoDB TTL and geospatial queries, simulating full Daily Night Routine workflows, or chaos-testing resilience.
Implement ACID transactions and advanced indexing for MongoDB at scale. Use when: ensuring data consistency across multi-document updates (user wallet + savings), designing query-specific indexes (compound, covered, geospatial), or optimizing API Gateway response times.
Implement fault-tolerant RabbitMQ consumers for distributed systems. Use when: building Python workers (Scraper, Personalization) that must survive crashes, handle duplicate messages, and gracefully reject malformed payloads without data loss.