All Skills

Installation step patterns for Gentleman.Dots TUI installer. Trigger: When editing installer.go, adding installation steps, or modifying the installation flow.

Go testing patterns for Gentleman.Dots, including Bubbletea TUI testing. Trigger: When writing Go tests, using teatest, or adding test coverage.

Docker-based E2E testing patterns for Gentleman.Dots installer. Trigger: When editing files in installer/e2e/, writing E2E tests, or adding platform support.

Develop custom native UI libraries based on Flutter widgets for WebF. Create reusable component libraries that wrap Flutter widgets as web-accessible custom elements. Use when building UI libraries, wrapping Flutter packages, or creating native component systems.

Check Web API and CSS feature compatibility in WebF - determine what JavaScript APIs, DOM methods, CSS properties, and layout modes are supported. Use when planning features, debugging why APIs don't work, or finding alternatives for unsupported features like IndexedDB, WebGL, float layout, or CSS Grid.

Understand and work with WebF's async rendering model - handle onscreen/offscreen events and element measurements correctly. Use when getBoundingClientRect returns zeros, computed styles are incorrect, measurements fail, or elements don't layout as expected.

Develop custom WebF native plugins based on Flutter packages. Create reusable plugins that wrap Flutter/platform capabilities as JavaScript APIs. Use when building plugins for native features like camera, payments, sensors, file access, or wrapping existing Flutter packages.

Setup hybrid routing with native screen transitions in WebF - configure navigation using WebF routing instead of SPA routing. Use when setting up navigation, implementing multi-screen apps, or when react-router-dom/vue-router doesn't work as expected.

Create high-performance infinite scrolling lists with pull-to-refresh and load-more capabilities using WebFListView. Use when building feed-style UIs, product catalogs, chat messages, or any scrollable list that needs optimal performance with large datasets.

Setup and use WebF's Cupertino UI library to build native iOS-style UIs with pre-built components instead of crafting everything with HTML/CSS. Use when building iOS apps, adding native UI components, or improving UI performance.

Get started with WebF development - setup WebF Go, create a React/Vue/Svelte project with Vite, and load your first app. Use when starting a new WebF project, onboarding new developers, or setting up development environment.

You are an expert in prompt engineering, specializing in optimizing AI code assistant instructions. Your task is to analyze and improve the instructio

Install WebF native plugins to access platform capabilities like sharing, payment, camera, geolocation, and more. Use when building features that require native device APIs beyond standard web APIs.

Use this skill for general PostgreSQL table design. **Trigger when user asks to:** - Design PostgreSQL tables, schemas, or data models when creating new tables and when modifying existing ones. - Choose data types, constraints, or indexes for PostgreSQL - Create user tables, order tables, reference tables, or JSONB schemas - Understand PostgreSQL best practices for normalization, constraints, or indexing - Design update-heavy, upsert-heavy, or OLTP-style tables **Keywords:** PostgreSQL schema, table design, data types, PRIMARY KEY, FOREIGN KEY, indexes, B-tree, GIN, JSONB, constraints, normalization, identity columns, partitioning, row-level security Comprehensive reference covering data types, indexing strategies, constraints, JSONB patterns, partitioning, and PostgreSQL-specific best practices.

Use this skill to analyze an existing PostgreSQL database and identify which tables should be converted to Timescale/TimescaleDB hypertables. **Trigger when user asks to:** - Analyze database tables for hypertable conversion potential - Identify time-series or event tables in an existing schema - Evaluate if a table would benefit from Timescale/TimescaleDB - Audit PostgreSQL tables for migration to Timescale/TimescaleDB/TigerData - Score or rank tables for hypertable candidacy **Keywords:** hypertable candidate, table analysis, migration assessment, Timescale, TimescaleDB, time-series detection, insert-heavy tables, event logs, audit tables Provides SQL queries to analyze table statistics, index patterns, and query patterns. Includes scoring criteria (8+ points = good candidate) and pattern recognition for IoT, events, transactions, and sequential data.

Use this skill for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search. **Trigger when user asks to:** - Store or search vector embeddings in PostgreSQL - Set up semantic search, similarity search, or nearest neighbor search - Create HNSW or IVFFlat indexes for vectors - Implement RAG (Retrieval Augmented Generation) with PostgreSQL - Optimize pgvector performance, recall, or memory usage - Use binary quantization for large vector datasets **Keywords:** pgvector, embeddings, semantic search, vector similarity, HNSW, IVFFlat, halfvec, cosine distance, nearest neighbor, RAG, LLM, AI search Covers: halfvec storage, HNSW index configuration (m, ef_construction, ef_search), quantization strategies, filtered search, bulk loading, and performance tuning.

Comprehensive PostGIS spatial table design reference covering geometry types, coordinate systems, spatial indexing, and performance patterns for location-based applications

Use this skill to migrate identified PostgreSQL tables to Timescale/TimescaleDB hypertables with optimal configuration and validation. **Trigger when user asks to:** - Migrate or convert PostgreSQL tables to hypertables - Execute hypertable migration with minimal downtime - Plan blue-green migration for large tables - Validate hypertable migration success - Configure compression after migration **Prerequisites:** Tables already identified as candidates (use find-hypertable-candidates first if needed) **Keywords:** migrate to hypertable, convert table, Timescale, TimescaleDB, blue-green migration, in-place conversion, create_hypertable, migration validation, compression setup Step-by-step migration planning including: partition column selection, chunk interval calculation, PK/constraint handling, migration execution (in-place vs blue-green), and performance validation queries.

Use this skill to implement hybrid search combining BM25 keyword search with semantic vector search using Reciprocal Rank Fusion (RRF). **Trigger when user asks to:** - Combine keyword and semantic search - Implement hybrid search or multi-modal retrieval - Use BM25/pg_textsearch with pgvector together - Implement RRF (Reciprocal Rank Fusion) for search - Build search that handles both exact terms and meaning **Keywords:** hybrid search, BM25, pg_textsearch, RRF, reciprocal rank fusion, keyword search, full-text search, reranking, cross-encoder Covers: pg_textsearch BM25 index setup, parallel query patterns, client-side RRF fusion (Python/TypeScript), weighting strategies, and optional ML reranking.

Use this skill when creating database schemas or tables for Timescale, TimescaleDB, TigerData, or Tiger Cloud, especially for time-series, IoT, metrics, events, or log data. Use this to improve the performance of any insert-heavy table. **Trigger when user asks to:** - Create or design SQL schemas/tables AND Timescale/TimescaleDB/TigerData/Tiger Cloud is available - Set up hypertables, compression, retention policies, or continuous aggregates - Configure partition columns, segment_by, order_by, or chunk intervals - Optimize time-series database performance or storage - Create tables for sensors, metrics, telemetry, events, or transaction logs **Keywords:** CREATE TABLE, hypertable, Timescale, TimescaleDB, time-series, IoT, metrics, sensor data, compression policy, continuous aggregates, columnstore, retention policy, chunk interval, segment_by, order_by Step-by-step instructions for hypertable creation, column selection, compression policies, retention, continuous aggregates, and indexes.

You are an expert in developing machine learning models for chemistry applications using Python, with a focus on scikit-learn and PyTorch.

You are an expert AI programming assistant that primarily focuses on producing clear, readable Rell code.

ASSISTANT RULES

Use the project specifications and guidelines to build the Todo app.