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Found 119 Skills
Performant React forms with minimal re-renders and built-in validation
This skill should be used when the user asks to "integrate Gemini review", "merge Gemini suggestions", "add Gemini comments to PR review", "sync Gemini code assist", "combine Gemini feedback", or mentions integrating gemini-code-assist suggestions into the PR review comment. Fetches Gemini Code Assist review comments and integrates non-duplicate, non-outdated suggestions into the pr-review-and-document PR comment.
Go (Golang) naming conventions — covers packages, constructors, structs, interfaces, constants, enums, errors, booleans, receivers, getters/setters, functional options, acronyms, test functions, and subtest names. Use this skill when writing new Go code, reviewing or refactoring, choosing between naming alternatives (New vs NewTypeName, isConnected vs connected, ErrNotFound vs NotFoundError, StatusReady vs StatusUnknown at iota 0), debating Go package names (utils/helpers anti-patterns), or asking about Go naming best practices. Also trigger when the user mentions MixedCaps vs snake_case, ALL_CAPS constants, Get-prefix on getters, or error string casing. Do NOT use for general Go implementation questions that don't involve naming decisions.
Technical analysis patterns - Elliott Wave, Wyckoff, Fibonacci, Markov Regime, and Turtle Trading with confluence detection. Use when analyzing charts, identifying trading signals, or calculating technical levels.
Skill for building platform-independent design systems. Develops consistent component libraries for all UI frameworks. Use proactively when user needs consistent UI components or mentions design tokens. Triggers: design system, component library, design tokens, shadcn, 디자인 시스템, デザインシステム, 设计系统, sistema de diseño, biblioteca de componentes, tokens de diseño, système de design, bibliothèque de composants, jetons de design, Design-System, Komponentenbibliothek, Design-Tokens, sistema di design, libreria di componenti, token di design Do NOT use for: one-off UI changes, backend development, or simple static sites.
Riot 공식 LoL Esports 데이터와 Oracle's Elixir 스타일 historical 데이터로 LCK 경기 결과, 현재 순위, live turning point, 밴픽 matchup/synergy, patch meta, 팀 파워 레이팅을 조회한다.
Aurora Smart Home orchestrator — routing layer for all smart home skills. Use this skill when the user asks ANY smart home question and you need to decide which skill to invoke, or when a task spans multiple skills (e.g., "build a sensor that shows on a dashboard and triggers automations"). Invoke aurora FIRST before reaching for a specific skill — it will route to the right specialist(s) and recommend the correct Claude model to keep token usage efficient. Trigger on: smart home, Home Assistant, ESPHome, automation, IoT, dashboard, ESP32, Node-RED, or any request about controlling or monitoring devices at home.
Expert-level biology, biotechnology, genetics, bioinformatics, and computational biology
Time-series database implementation for metrics, IoT, financial data, and observability backends. Use when building dashboards, monitoring systems, IoT platforms, or financial applications. Covers TimescaleDB (PostgreSQL), InfluxDB, ClickHouse, QuestDB, continuous aggregates, downsampling (LTTB), and retention policies.
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 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.
Design predictive maintenance strategies using sensor data, ML models for remaining useful life (RUL), and the P-F curve framework. Use this skill when the user needs to reduce unplanned downtime, transition from reactive to predictive maintenance, evaluate sensor/IoT investments, or estimate equipment failure probability — even if they say 'machines keep breaking down', 'when will this equipment fail', 'should we invest in IoT sensors', or 'reduce unplanned downtime'.