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Found 2,439 Skills
Use when a task has multiple independent subtasks that can be executed concurrently by separate agents. Triggers when decomposed work has 2+ subtasks with no data dependencies, when subtasks operate on different files or codebase sections, when serial execution time would be significantly longer than parallel, or when independent analyses or deliverables need concurrent generation.
Choose and refactor visionOS app architecture across surfaces, scene boundaries, state ownership, and file layout. Use when deciding window vs volume vs immersive space, splitting a feature across scenes, cleaning up a monolithic spatial root, or defining the ownership map before implementing SwiftUI or RealityKit details.
Design and redesign EdgeSpark frontends with distinctive, production-grade visual direction instead of generic AI-looking UI. Use when building or polishing landing pages, marketing sites, dashboards, auth flows, portfolios, product surfaces, or reusable frontend sections in EdgeSpark, especially when the task mentions design quality, aesthetics, typography, color, layout, motion, art direction, or making the UI feel more premium and original.
Builds Moran's I spatial autocorrelation workflows in CARTO. Triggers when the user mentions spatial autocorrelation, Moran's I, spatial dependency, spatial correlation, spatial outliers, HH HL LH LL quadrants, high-high clusters, low-low clusters, spatial weight matrix, "is there clustering", "are values spatially correlated", local indicators of spatial association, LISA, spatial randomness test, or wants to determine whether a variable exhibits spatial clustering, dispersion, or randomness across a gridded dataset. Also relevant when the user needs to classify locations into cluster types (HH, HL, LH, LL) rather than just identifying hotspots and coldspots.
Sparse4D for multi-camera temporal 3D object detection and tracking. Uses sparse queries with deformable attention across camera views and time for end-to-end 3D perception, with an instance bank for temporal tracking. Use when training, evaluating, exporting, quantizing, or running inference for a TAO Sparse4D model. Trigger phrases include "train Sparse4D", "multi-camera 3D detection", "temporal 3D tracker", "sparse query 3D perception".
Spawn a single autonomous AI agent with a specific task, personality, and CLI backend (Claude, Gemini, OpenCode, Copilot). Agent accepts task from docs/todo/pending/, selects personality based on task type, and works autonomously with CLI tools. Integrates with docs-first workflow via task signals and progress tracking.
Google Workspace MCP integration for Gmail, Drive, Calendar, Docs, Sheets, Slides, Forms, Tasks, and Chat. Use when the user wants to read/send emails, manage files, create/edit documents, schedule events, or interact with any Google Workspace service.
Configure, explore, and optimize Nx monorepo workspaces. Use when setting up Nx, exploring workspace structure, configuring project boundaries, running tasks, analyzing affected projects, optimizing build caching, or implementing CI/CD with affected commands. Keywords - nx, monorepo, workspace, projects, targets, affected, build, lint, test.
Dispatch independent subagents in parallel for unrelated problems spanning different subsystems. Use when 2+ failures have independent root causes, multiple subsystems are broken independently, or user requests concurrent investigation. Use for "parallel", "multiple failures", "independent bugs", "fix these concurrently". Do NOT use for related failures, shared-state problems, or exploratory debugging where root cause is unknown.
Operate across Google Drive, Docs, Sheets, and Slides as one workflow surface for plans, trackers, decks, and shared documents. Use when the user needs to find, summarize, edit, migrate, or clean up Google Workspace assets without dropping to raw tool calls.
Use when you need to find which JAR contains a Java class, resolve import statements, identify classpath conflicts, or discover which dependency provides a class. Accepts fully qualified class names, simple class names, or partial patterns.
Run the SPARC Specification phase — gather requirements, define acceptance criteria, identify constraints, and store the spec in memory