Skill UI

Guides building and scaling Convex backends with TypeScript schemas, queries, mutations, real-time subscriptions, auth, file storage, scheduling, and deployment across React, Next.js, Angular, Vue, Svelte, and RN.

This skill provides a robust methodology for performing end-to-end UI testing and verification on Android emulators. Utilizing ADB commands, users can autonomously inspect UI element bounds (via uiautomator), simulate interactions (taps, swipes, input text), and capture visual/analytical screenshots. It is ideal for verifying UI changes in React Native or native Android applications, speeding up the debugging process, and generating comprehensive documentation for pull requests.

Transforms a single idea or asset into platform-native social posts, threads, scripts, calendars, and repurposed content for X, LinkedIn, TikTok, YouTube, and newsletters while keeping hooks, CTAs, and tone tailored to each destination.

Transforms natural-language prompts into Excalidraw JSON diagrams, supporting flowcharts, relationships, mind maps, architecture, DFD, swimlane, class, sequence, and ER views; ideal when users ask to visualize processes or system structures and need editable Excalidraw files.

Guides the Andru.ia systems engineer through the workflow of designing, documenting, and deploying new skills in the repository, enforcing the Antigravity anatomy and Diamond Standard while gathering a technical name, expert role, and outputs before writing README, registry snippet, and deployment steps.

Automatically scans modern API frameworks (Next.js, Express, FastAPI, Django) to generate comprehensive, ready-to-run test suites. It ensures complete coverage for critical areas including authentication, input validation (boundary/injection), error code matrices, pagination, file uploads, and rate limiting. Ideal for TDD, contract testing, and security audits.

This powerful tool helps translate natural language requirements into robust, normalized relational database schemas. It can generate comprehensive schema designs, complete with relationships, constraints, and advanced architectural concerns like multi-tenancy, soft deletes, and audit trails. Furthermore, it automates the generation of database migrations (supporting Prisma, TypeORM, Alembic, etc.), corresponding type definitions (TypeScript/Python), seed data, and Entity-Relationship Diagrams (ERD) using Mermaid.

GeoMaster is a comprehensive geospatial science skill that guides remote sensing, GIS, spatial analysis, and machine learning workflows for Earth observation and planetary data projects, covering satellite imagery, vector/raster math, point clouds, terrain, hydrology, and cloud-native data stacks.

Dispatching parallel agents lets you split independent investigations into focused prompts, coordinate isolated fixes concurrently, and review summaries for integration once each agent finishes.

Systematically verifies suspected security bugs to eliminate false positives and document evidence, guiding each finding through the standard or deep verification path and producing TRUE POSITIVE or FALSE POSITIVE verdicts.

Guides execution of implementation plans by dispatching isolated subagents per task, enforcing a spec-first then quality review loop, and preserving overall coordination context for faster, high-quality iterations.

Helps product managers diagnose whether AI workflows rely on indiscriminate context stuffing or deliberate context engineering, then apply bounded domains, retrieval, and Research→Plan→Reset→Implement practices to improve reliability and output quality.