# Framework & SEO Skills LLMS index: [llms.txt](/processkit/llms.txt) --- Skills for specific frameworks and search engine optimization. --- ### reflex-python > Reflex Python web framework for building full-stack apps in pure Python. Components, state management, and deployment. Use when building Reflex apps, designing component hierarchies, or managing app state. **Triggers:** When building web apps with Reflex, designing components, managing state, routing, or creating full-stack Python web applications. **Tools:** `Bash(reflex:*)` `Bash(python:*)` `Read` `Write` **References:** `component-reference.md` Key capabilities: - App structure: initialization, entry points, page decorators, file-based routing, configuration - Component system: layout (box, flex, grid), display (text, heading, image), input (input, select, checkbox), feedback (alert, toast, spinner) - State management with `rx.State` classes, typed vars, event handlers, computed vars, and substates - Event handling: on_click, on_change, two-way binding, background tasks, event chaining - Styling with Radix UI design tokens, responsive props, light/dark themes - Routing with dynamic segments, programmatic navigation, on_load events, and 404 handling - Database integration via built-in SQLModel with automatic migrations - Deployment to Reflex Cloud or self-hosted via Docker ??? example "Example usage" **Build a todo app:** Defines a `TodoState` with a list of todos and input field, creates event handlers for add/delete/toggle, builds UI with `rx.input`, `rx.button`, and `rx.foreach(TodoState.todos, render_todo)` to render the list dynamically. --- ### fastapi-patterns > FastAPI patterns including dependency injection, Pydantic models, async endpoints, middleware, and testing. Use when building FastAPI applications, designing API endpoints, or reviewing FastAPI code. **Triggers:** When building APIs with FastAPI, designing endpoints, implementing dependency injection, authentication, or testing FastAPI applications. **Tools:** `Bash(python:*)` `Bash(uvicorn:*)` `Read` `Write` **References:** `endpoint-patterns.md` Key capabilities: - Route definitions with HTTP method decorators, path/query parameters, and APIRouter modules - Pydantic models for request/response: separate Create/Update/Response schemas, validation with Field() - Dependency injection with `Depends()`, chained dependencies, `Annotated` for reusable deps, yield-based cleanup - Async endpoint patterns: when to use `async def` vs `def`, pairing with async libraries - Middleware: CORS, custom timing, trusted hosts, GZip compression - Authentication: OAuth2 password flow, JWT decoding, API key headers, scopes - Background tasks, WebSocket support, and structured error handling - Testing with TestClient, dependency overrides, async tests, and WebSocket testing ??? example "Example usage" **REST API for a blog:** Creates Pydantic schemas for `PostCreate`, `PostResponse`, `CommentCreate`, defines APIRouter modules for `/posts` and `/posts/{id}/comments`, implements CRUD handlers with SQLAlchemy dependency injection, and adds pagination to list endpoints. --- ### pandas-polars > DataFrame operations with pandas and polars including groupby, joins, reshaping, and performance optimization. Use when manipulating tabular data, choosing between pandas and polars, or optimizing DataFrame code. **Triggers:** When working with tabular data, performing DataFrame operations, data transformations, cleaning data, aggregating by group, or choosing between pandas and polars. **Tools:** `Bash(python:*)` `Read` `Write` **References:** `api-comparison.md` Key capabilities: - Choosing between pandas (mature ecosystem, exploratory work, <1GB) and polars (faster, lower memory, lazy evaluation, 1GB+) - DataFrame I/O: Parquet over CSV, dtype enforcement, chunked reading, column selection - Selection and filtering with expressions (polars) and `.loc[]`/`.iloc[]` (pandas) - GroupBy and aggregation with named columns, window functions (`over()` in polars) - Joins and merges with explicit join types, duplicate checking, anti-joins - Reshaping with pivot and melt/unpivot for wide and long formats - Missing data handling: null counts, fill strategies, interpolation - String and datetime operations across both libraries - Performance optimization: lazy evaluation, avoiding `apply()`, categorical dtypes ??? example "Example usage" **Process a large CSV with group statistics:** Uses polars lazy mode to scan the CSV, applies filters before collection, groups by the requested column with multiple aggregations in one `.agg()` call, sorts results, and writes output to Parquet for downstream use. --- ### flutter-development > Flutter/Dart development including widget architecture, state management, navigation, and cross-platform patterns. Use when building Flutter apps, choosing state management, or designing responsive mobile layouts. **Triggers:** When building mobile or cross-platform apps with Flutter, designing widgets, managing state, adding navigation, or creating responsive layouts. **Tools:** `Bash(flutter:*)` `Bash(dart:*)` `Read` `Write` **References:** `widget-catalog.md` Key capabilities: - Widget architecture: StatelessWidget vs StatefulWidget, composition over inheritance, const constructors - Layout system: Row, Column, Expanded, Flexible, Stack, ListView.builder, responsive design with LayoutBuilder - State management options: setState (local), Provider (lightweight DI), Riverpod (type-safe), BLoC (event-driven) - Navigation with GoRouter: declarative routes, nested navigation with ShellRoute, redirect guards, deep linking - Theming with Material 3, ColorScheme.fromSeed, dark mode support, custom TextTheme - Networking with http/dio, json_serializable, FutureBuilder/StreamBuilder, repository pattern - Platform channels for native code integration (MethodChannel, EventChannel) - Testing: unit, widget (testWidgets, pumpWidget), integration, and golden tests - Performance: const widgets, ListView.builder, RepaintBoundary, DevTools profiling ??? example "Example usage" **Product list with search and pull-to-refresh:** Creates a StatefulWidget with a search TextField, uses ListView.builder for efficient rendering, implements RefreshIndicator for pull-to-refresh, fetches products from a repository, and shows loading/error/empty states. --- ### seo-optimization > SEO optimization including on-page SEO, technical SEO, Core Web Vitals, structured data, and mobile-first indexing. Use when optimizing websites for search engines, implementing structured data, or improving page performance. **Triggers:** When optimizing a website for search engines, working with meta tags, structured data, page speed, Core Web Vitals, or mobile-first indexing. **Tools:** `Bash(curl:*)` `Bash(lighthouse:*)` `Read` `Write` **References:** `technical-seo-checklist.md` Key capabilities: - On-page SEO: title tags, meta descriptions, heading hierarchy, alt text, internal links, URL structure - Technical SEO: robots.txt, XML sitemaps, canonical URLs, hreflang, redirect chains, index control - Structured data with JSON-LD: Article, Product, FAQ, BreadcrumbList, Organization schemas - Core Web Vitals optimization: LCP (<2.5s), INP (<200ms), CLS (<0.1) with specific fix strategies - Page speed: render-blocking resources, image compression (WebP/AVIF), CDN, minification, Brotli/gzip - Mobile-first indexing: responsive design, viewport meta, touch targets, content parity - Internal linking strategy: content hubs, descriptive anchor text, orphan page detection - Security and trust signals: HTTPS, HSTS, E-E-A-T authorship ??? example "Example usage" **SEO audit of a Next.js site:** Checks meta tags on key pages, verifies sitemap.xml and robots.txt, validates structured data with Rich Results Test, runs Lighthouse for Core Web Vitals, checks canonical URLs, and produces a prioritized list of fixes sorted by expected impact.