productivity▌

AI-powered business analysis with dashboards, predictive models, and data-driven strategic recommendations. \n \n Covers modern BI platforms (Tableau, Power BI, Looker, Qlik Sense) and cloud analytics (Snowflake, BigQuery, Databricks) with real-time visualization and automated reporting \n Includes KPI framework design, OKR development, balanced scorecards, and financial modeling for revenue forecasting, CLV optimization, and scenario planning \n Provides customer analytics capabilities: segment

Debug logging utility with namespace-based filtering across desktop, server, and client environments. \n \n Follows strict namespace conventions (e.g., lobe-server:[module] , lobe-desktop:[module] ) to organize logs by platform and module \n Supports format specifiers including %O for expanded objects, %s for strings, and %d for numbers \n Enable output via localStorage.debug in browsers, DEBUG environment variable in Node.js, or process.env.DEBUG in Electron \n Wildcard filtering (e.g., lobe-*

Annotation-driven caching abstraction for Spring Boot service methods with multi-provider support. \n \n Supports multiple cache providers (ConcurrentMap, Caffeine, Redis, Ehcache, JCache) via pluggable CacheManager beans without changing business code \n Provides @Cacheable , @CachePut , @CacheEvict , and @Caching annotations with SpEL-based key generation, conditional caching, and synchronization control \n Includes configuration patterns for TTL, capacity limits, and scheduled eviction; integ

Full-text search across past Claude Code and Codex sessions with BM25 ranking and flexible query syntax. \n \n Supports keyword search, exact phrases, boolean operators (AND, OR, NOT), and prefix matching across all indexed conversations \n Filters results by project path, recency (days), and source (Claude Code or Codex sessions) \n Includes session resumption commands and a transcript reader to view raw conversation files \n Automatically indexes user and assistant messages from ~/.claude/proj

Tinybird configuration rules, SQL patterns, and optimization guidance for datasources, pipes, endpoints, and materialized views. \n \n Covers 13 rule categories including project structure, datasource and pipe design, endpoint schemas, materialized views, copy pipes, connections, SQL best practices, and deduplication patterns \n Emphasizes local files as source of truth, MergeTree as default table engine, and SELECT-only SQL with strict parameter handling \n Provides optimization strategies: fil

Skill by ara.so — Daily 2026 Skills collection.

AI-powered documentation search and Q&A for GitHub repositories via DeepWiki. \n \n Three command modes: ask natural-language questions about repository code and docs, browse wiki structure and topics, or read full documentation contents \n Supports single or multiple repositories (up to 10) in a single query for comparative analysis \n AI-generated answers are grounded in actual repository documentation, with minimum 1-minute timeout for response generation \n Works with any public GitHub

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Help plan, execute, and synthesize user research studies.

State management and thread/message access layer for assistant-ui chat applications. \n \n Provides three runtime types: AssistantRuntime for overall state, ThreadRuntime for current conversation, and ThreadListRuntime for managing multiple threads \n Access state via useAuiState selectors and perform operations through useAui() API (append messages, cancel runs, edit/reload messages, query capabilities) \n Emit and listen to lifecycle events: thread.runStart , thread.runEnd , composer.send , an