productivity▌

Use this skill to pull English (or any source locale) App Store metadata, translate it with LLM, and push translations back to App Store Connect — all automated.

Structured discovery interview planning with adaptive methodology selection based on research goals and constraints. \n \n Guides product managers through four adaptive questions to define research goals, target segments, access constraints, and interview methodology \n Generates tailored interview frameworks with 5+ context-specific questions, follow-ups, and bias-avoidance guidance for each methodology (Mom Test, Jobs-to-be-Done, switch interviews, timeline mapping) \n Includes opening/closing

Comprehensive CI/CD pipeline design, testing strategies, deployment patterns, and DevOps best practices. \n \n Covers five core pipeline stages: build, test, security scanning, staging deployment, and production deployment with examples for each \n Includes four deployment strategies: blue-green, canary, rolling, and feature flags for zero-downtime releases and gradual rollouts \n Provides testing pyramid guidance with unit, integration, and end-to-end test layers, plus parallelization and flaky

Client-side tracking with Analytics.js. Include track, identify, page, and group calls. Anonymous ID persists until identify merges with user.

When working on the Agents workbench layout, always follow these guidelines:

Brainstorm unique, memorable product names with rationale aligned to brand values and target audience. Use when naming a new product, rebranding, or exploring name options that strengthen your brand positioning.

Fault tolerance and resilience patterns for Spring Boot microservices using Resilience4j. \n \n Provides six core patterns: circuit breaker, retry with exponential backoff, rate limiter, bulkhead (semaphore and thread pool), time limiter, and fallback mechanisms \n Annotation-based integration with Spring Boot 3.x AOP; patterns can be stacked on single methods for comprehensive fault tolerance \n Includes configuration examples for all patterns in YAML, with health indicator and Actuator endpoin

Automated code review across TypeScript, JavaScript, Python, Swift, Kotlin, and Go with quality analysis and security scanning. \n \n Three core scripts: PR analyzer for automated scaffolding, code quality checker for deep analysis and performance metrics, and review report generator for structured output \n Includes comprehensive reference documentation covering code review checklists, coding standards, and common antipatterns with real-world examples \n Supports modern tech stacks including Re

INVEST-compliant user story generation, sprint planning, and backlog management for agile teams. \n \n Generates well-formed user stories with automatic acceptance criteria from epics, validated against INVEST principles \n Includes sprint capacity planning, point estimation, and priority assignment to streamline sprint execution \n Provides velocity tracking and backlog prioritization metrics for stakeholder communication and agile ceremonies \n Core functionality accessible via Python scripts

Systematically address GitHub PR review comments and issue feedback using the gh CLI. \n \n Fetches and inspects PR comments and review threads to understand feedback before applying fixes \n Guides categorization and planning of comments, with user confirmation checkpoints for prioritization \n Applies code changes and responds to comment threads as resolved using gh CLI commands \n Requires gh authentication; includes auth status verification as a prerequisite step \n