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Found 1,934 Skills
Drop-in pandas replacement with ClickHouse performance. Use `import chdb.datastore as pd` (or `from datastore import DataStore`) and write standard pandas code — same API, 10-100x faster on large datasets. Supports 16+ data sources (MySQL, PostgreSQL, S3, MongoDB, ClickHouse, Iceberg, Delta Lake, etc.) and 10+ file formats (Parquet, CSV, JSON, Arrow, ORC, etc.) with cross-source joins. Use this skill when the user wants to analyze data with pandas-style syntax, speed up slow pandas code, query remote databases or cloud storage as DataFrames, or join data across different sources — even if they don't explicitly mention chdb or DataStore. Do NOT use for raw SQL queries, ClickHouse server administration, or non-Python languages.
Write, validate, and optimise PromQL queries for Prometheus and Grafana Cloud Metrics. Use when the user asks to query metrics, write a PromQL expression, calculate rates, aggregate across labels, build histogram quantiles, create recording rules, debug query performance, or understand metric cardinality. Triggers on phrases like "PromQL", "Prometheus query", "write a metric query", "calculate rate", "histogram_quantile", "recording rule", "metric cardinality", "sum by", "rate vs irate", "absent()", or "query is slow".
Use when building, fixing, or improving ANY SwiftUI UI — views, navigation, layout, animations, performance, architecture, gestures, debugging, iOS 26 features.
Building decay and upkeep systems for survival games. Use when implementing timer-based decay, Tool Cupboard patterns (Rust-style protection radius), resource upkeep costs, or server performance management through automatic cleanup. Balances gameplay and server health.
Grafana Pyroscope continuous profiling platform. Covers instrumentation of Go/Java/Python/Ruby/Node.js/ .NET/Rust apps via SDKs or eBPF (Alloy), flame graph analysis, ProfileQL queries, server configuration and architecture, Grafana Cloud Profiles integration, and trace-profile linking (Span Profiles). Use when working with profiling data, instrumenting apps for Pyroscope, analyzing performance profiles, or deploying Pyroscope server.
Grafana Tempo distributed tracing backend. Covers TraceQL query language (span selectors, attribute scopes, pipeline operators, structural operators, metrics functions), trace ingestion via OTLP/Jaeger/Zipkin, Tempo architecture (distributor/ingester/compactor/querier/metrics-generator), full configuration reference with YAML, metrics-from-traces (span metrics, service graphs, TraceQL metrics), deployment modes (monolithic/microservices/Helm/Kubernetes), multi-tenancy, performance tuning, caching, and HTTP API. Use when working with distributed traces, writing TraceQL queries, deploying Tempo, configuring trace pipelines, or setting up Grafana-Tempo integrations (traces-to-logs, traces-to-metrics, traces-to-profiles).
Follow this sub-process for code optimization — handle tasks where 'behavior remains unchanged but structure changes' (structure / performance / readability). Shift single-module internal optimization from 'AI random refactoring' to 'first scan to generate a checklist, confirm each item with the user, execute step by step according to the method library, and obtain manual approval for each step'. Trigger scenarios: When the user mentions phrases like 'optimize / refactor / rewrite / split / poor performance / too long code' without any accompanying behavior changes. Do not handle new requirements (route to feature), bugs (route to issue), or cross-module architecture restructuring (route to architecture + decisions).
Triage mixed game demo and playtest feedback into a prioritized fix brief, weighted evidence summary, and next artifact recommendation. Use when a team has playtest notes, Steam Playtest responses, creator or streamer demo reactions, survey comments, wishlist/context signals, bug lists, or performance findings and needs to decide what to fix first before the next build, festival, or launch beat, even if they only say "sort our playtest feedback", "what should we fix before Next Fest", "players are confused", "streamers bounced off the demo", or "turn these demo notes into priorities".
Refactor Flutter/Dart code to improve maintainability, readability, and performance. This skill applies Dart 3 features like records, patterns, and sealed classes, implements proper state management with Riverpod or BLoC, and uses Freezed for immutable models. It addresses monolithic widgets, missing const constructors, improper BuildContext usage, and deep nesting. Apply when you notice widgets doing too much, performance issues from unnecessary rebuilds, or legacy Dart 2 patterns.
Use when build times are slow, investigating build performance, analyzing Build Timeline, identifying type checking bottlenecks, enabling compilation caching, or optimizing incremental builds - comprehensive build optimization workflows including Xcode 26 compilation caching
Debug Angular applications systematically with expert-level diagnostic techniques. This skill provides comprehensive guidance for troubleshooting dependency injection errors, change detection issues (NG0100), RxJS subscription leaks, lazy loading failures, zone.js problems, and common Angular runtime errors. Includes structured four-phase debugging methodology, Angular DevTools usage, console debugging utilities (ng.probe), and performance profiling strategies for modern Angular applications.
Refactor React and TypeScript code to improve maintainability, readability, and performance. This skill transforms complex React components into clean, well-structured code following modern React 19 patterns. It addresses component bloat, prop drilling, unnecessary re-renders, and improper hook usage. Leverages React 19 features including the React Compiler for automatic memoization, Actions for form handling, useOptimistic for immediate UI feedback, the use() hook for async data, and Server Components for optimal performance.