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Found 430 Skills
Anthropic Claude Agent SDK for autonomous agents and multi-step workflows. Use for subagents, tool orchestration, MCP servers, or encountering CLI not found, context length exceeded errors.
Expert cuTile programming assistant. Write high-performance GPU kernels using cuTile's tile-based programming model with proper validation and optimization. Supports deep agent orchestration for complex multi-kernel tasks.
Monorepo management (Nx, Turborepo, pnpm workspaces) — task orchestration, caching, code sharing. Use when setting up monorepo, optimizing builds, or managing multi-package projects.
Guides agents in compiling and packaging C/C++ source code into dynamic or static libraries (Code Assets) using Dart's Native Assets hook system (via hook/build.dart and hook/link.dart utilizing package:hooks and package:native_toolchain_c). Use when a user asks to: 'setup native assets', 'compile C/C++ source code', 'bundle dynamic libraries', 'build native C code', 'link native assets', 'implement build.dart or link.dart hooks', or 'integrate C/C++ interop in Dart/Flutter'. Helps agents avoid manual toolchain orchestration and configures secure hash-validated binary downloads or advanced linker tree-shaking with package:record_use mapping.
Design durable workflows with Temporal for distributed systems. Covers workflow vs activity separation, saga patterns, state management, and determinism constraints. Use when building long-running processes, distributed transactions, or microservice orchestration.
Design and build AI agents for any domain. Use when users: (1) ask to "create an agent", "build an assistant", or "design an AI system" (2) want to understand agent architecture, agentic patterns, or autonomous AI (3) need help with capabilities, subagents, planning, or skill mechanisms (4) ask about Claude Code, Cursor, or similar agent internals (5) want to build agents for business, research, creative, or operational tasks Keywords: agent, assistant, autonomous, workflow, tool use, multi-step, orchestration
Comprehensive ADB (Android Debug Bridge) automation skill for game bot development, device management, computer vision integration, and Tauri-Python orchestration. Provides modular expertise for building intelligent Android automation workflows.
Build durable, long-running workflows on Cloudflare Workers with automatic retries, state persistence, and multi-step orchestration. Supports step.do, step.sleep, step.waitForEvent, and runs for hours to days. Use when: creating long-running workflows, implementing retry logic, building event-driven processes, coordinating API calls, scheduling multi-step tasks, or troubleshooting NonRetryableError, I/O context, serialization errors, or workflow execution failures. Keywords: cloudflare workflows, workflows workers, durable execution, workflow step, WorkflowEntrypoint, step.do, step.sleep, workflow retries, NonRetryableError, workflow state, wrangler workflows, workflow events, long-running tasks, step.sleepUntil, step.waitForEvent, workflow bindings
Docker containerization patterns for Python/React projects. Use when creating or modifying Dockerfiles, optimizing image size, setting up Docker Compose for local development, or hardening container security. Covers multi-stage builds for Python (python:3.12-slim) and React (node:20-alpine -> nginx:alpine), layer optimization, .dockerignore, non-root user, security scanning with Trivy, Docker Compose for dev (backend + frontend + PostgreSQL + Redis), and image tagging strategy. Does NOT cover deployment orchestration (use deployment-pipeline).
Temporal.io workflow orchestration for durable, fault-tolerant distributed applications. Use when implementing long-running workflows, saga patterns, microservice orchestration, or systems requiring exactly-once execution guarantees.
Multi-agent orchestration workflow for deep research: Split a research objective into parallel sub-objectives, run sub-processes using Claude Code non-interactive mode (`claude -p`); prioritize installed skills for network access and data collection, followed by MCP tools; aggregate sub-results with scripts and refine them chapter by chapter, and finally deliver "finished report file path + summary of key conclusions/recommendations". Applicable scenarios: systematic web/data research, competitor/industry analysis, batch link/dataset shard retrieval, long-form writing and evidence integration, or scenarios where users mention "deep research/Deep Research/Wide Research/multi-agent parallel research/multi-process research".
Use when coordinating complex tasks with orchestration, delegation, or parallel workstreams - provides structured workflows for orchestrate:brainstorm, orchestrate:spawn, and orchestrate:task.