productivity▌

Amplify safe or generic designs with intentional drama, distinctive choices, and visual confidence while maintaining usability. \n \n Systematically increases impact across typography, color, spatial composition, motion, and visual effects to create memorable experiences \n Guides away from AI design clichés (cyan gradients, glassmorphism, neon accents) toward distinctive, purposeful amplification \n Requires design context analysis first—assesses brand personality, purpose, audience, and constr

Generate customizable article cover images across 5 independent dimensions and 3 aspect ratios. \n \n Combines 6 image types (hero, conceptual, typography, metaphor, scene, minimal) with 10 color palettes and 7 rendering styles for fine-grained visual control \n Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects, plus additional ratios (4:3, 3:2, 3:4) \n Auto-analyzes article content to recommend dimensions, or accepts explicit flags for type, palette, rendering, text level

Complete Better Auth server and client setup with database adapters, session management, plugins, and security configuration. \n \n Covers full workflow from installation through database migration, environment variable setup, and route handler creation across multiple frameworks \n Supports multiple database adapters (Prisma, Drizzle, MongoDB, direct connections) with critical guidance on model vs. table naming conventions \n Includes session storage strategies with secondary storage (Redis/KV)

Dispatch fresh subagents per task with two-stage review (spec compliance, then code quality) in the current session. \n \n Isolates each task to a dedicated subagent with precisely crafted context, preventing context pollution and keeping the controller focused on coordination \n Enforces a two-stage review cycle: spec compliance reviewer confirms the implementation matches requirements, then code quality reviewer checks for issues \n Handles implementer status signals (DONE, DONE_WITH_CONCERNS,

Visual verification workflow for UI changes to accelerate code review and catch responsive design issues early.

Transform genome-wide association studies (GWAS) into actionable drug targets and repurposing opportunities.

Monitoring deployed machine learning models ensures they continue to perform well in production, detecting data drift, concept drift, and performance degradation.

Modern file and content search.

Systematic memory management for agents through daily logging, session preservation, and knowledge extraction.

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