productivity▌

Per-model cost summaries from CodexBar CLI logs for Codex or Claude providers. \n \n Supports two summary modes: \"current\" (most recent daily model with highest cost) and \"all\" (full model breakdown across all logged days) \n Accepts input via live CodexBar CLI invocation, JSON file, or stdin; outputs as plain text or formatted JSON \n Requires CodexBar CLI installed locally (macOS only via Homebrew; Linux support pending) \n Falls back to last entry in modelsUsed when model breakdowns are u

Swift Concurrency review and remediation for Swift 6.2+ codebases. \n \n Diagnoses and fixes actor isolation, Sendable safety, and data-race warnings through targeted edits that preserve existing behavior \n Applies minimal, concrete fixes: @MainActor annotations, actor isolation, Sendable conformance, and completion-handler-to-async/await migrations \n Triages compiler diagnostics by checking project concurrency settings, actor context, and whether code is UI-bound or background work \n Verifie

Patterns for structured concurrency, Flow-based reactive streams, and coroutine testing in Android and Kotlin Multiplatform projects.

Write correct, performant SQL across all major data warehouse dialects. \n \n Covers five major dialects: PostgreSQL, Snowflake, BigQuery, Redshift, and Databricks with dialect-specific syntax for date/time, string functions, arrays, and JSON handling \n Includes common analytical patterns: window functions, CTEs, cohort retention, funnel analysis, and deduplication with ready-to-use examples \n Provides performance optimization tips per dialect, such as clustering keys in Snowflake, partition p

Automated analysis of market-moving news from the past 10 days with impact-ranked reporting. \n \n Collects news across six categories (monetary policy, inflation, earnings, geopolitical, commodities, corporate) using WebSearch and WebFetch, prioritizing Tier 1 sources \n Ranks events by impact score combining price movement magnitude, breadth across asset classes, and forward-looking significance \n Analyzes multi-asset reactions (equities, bonds, commodities, currencies) and compares actual ma

Declarative UI toolkit for building native Android interfaces with state management and recomposition optimization. \n \n Provides state management primitives: remember for recomposition survival, rememberSaveable for configuration changes, mutableStateOf for observable state, and derivedStateOf for computed values \n Emphasizes state hoisting to create stateless, reusable composables and integrates with ViewModel and StateFlow for app-level state \n Includes efficient recomposition patterns usi

Statistical methods for descriptive analysis, trend detection, outlier identification, and hypothesis testing with practical business interpretation. \n \n Covers descriptive statistics (mean, median, percentiles, spread measures), trend analysis with moving averages and period-over-period comparisons, and simple forecasting methods for business analysts \n Includes three outlier detection approaches (z-score, IQR, percentile methods) with guidance on investigating and handling anomalies rather

Structured hiring framework from 94 product leaders to make stronger candidate decisions. \n \n Apply 12 core principles covering reference checks, work trials, agency assessment, and T-shaped hiring to evaluate candidates systematically \n Use diagnostic questions to understand hiring stage, team gaps, and whether decisions are based on structured rubrics or intuition alone \n Challenge common biases like pedigree shortcuts, gut-feel-only decisions, and unicorn hiring; prioritize references, pa

Complete App Store Optimization toolkit for researching, optimizing, and tracking mobile app performance across Apple App Store and Google Play Store. \n \n Covers keyword research, competitor analysis, metadata optimization (titles, descriptions, keywords), and visual asset strategies with platform-specific character limit validation \n Includes review sentiment analysis, rating improvement tactics, and A/B testing frameworks for continuous conversion optimization \n Provides ASO health scoring

Create and maintain minimal, high-signal agent documentation under 60 lines. \n \n Enforces research-backed best practices for agent-facing docs; instruction quality degrades with length \n Requires three core sections: Package Manager, File-Scoped Commands (per-file test/lint/typecheck), and Commit Attribution with agent identity \n Analyzes project structure (lock files, linter configs, CI commands, monorepo indicators) to determine what belongs in the file \n Uses headers and bullets only; re