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Found 41 Skills
Deploy agent to Databricks Apps using DAB (Databricks Asset Bundles). Use when: (1) User says 'deploy', 'push to databricks', or 'bundle deploy', (2) 'App already exists' error occurs, (3) Need to bind/unbind existing apps, (4) Debugging deployed apps, (5) Querying deployed app endpoints.
Wrap an existing Python agent as an Agent Stack service using agentstack-sdk server wrapper, without changing business logic.
AWS Bedrock AgentCore comprehensive expert for deploying and managing all AgentCore services. Use when working with Gateway, Runtime, Memory, Identity, or any AgentCore component. Covers MCP target deployment, credential management, schema optimization, runtime configuration, memory management, and identity services.
Build and deploy AI agents using VM0's agent-native infrastructure. This skill guides you through the complete agent creation workflow - from understanding requirements to deployment and scheduling.
VM0 CLI for building and running AI agents in secure sandboxes. Use this skill when users need to install vm0, create agent projects, deploy agents, run agents, manage volumes/artifacts.
Step-by-step guide for openclaw users to build, deploy, and monetise an AI agent with aixyz. Covers everything from zero: installing Bun, scaffolding an agent, choosing a deployment option, getting a crypto wallet, funding it for on-chain registration, and marketing your agent once it is live.
Autonomous AI agent platform for building and deploying continuous agents. Use when creating visual workflow agents, deploying persistent autonomous agents, or building complex multi-step AI automation systems.
Provision dedicated AI agents on AgentBox via x402 payment ($5 USDC on Solana). Use when creating cloud instances running OpenClaw AI gateways with HTTPS and web terminal. Requires Node.js and a Solana wallet.json with USDC funds. Covers: provisioning new instances, polling status, interacting via OpenAI-compatible chat completions, extending, and listing instances.
6-phase investigation workflow for understanding existing systems. Auto-activates for research tasks. Optimized for exploration and understanding, not implementation. Includes parallel agent deployment for efficient deep dives and automatic knowledge capture to prevent repeat investigations.
Migrate an MLflow ResponsesAgent from Databricks Model Serving to Databricks Apps. Use when: (1) User wants to migrate from Model Serving to Apps, (2) User has a ResponsesAgent with predict()/predict_stream() methods, (3) User wants to convert to @invoke/@stream decorators.
Use after analyze-and-document has generated CLAUDE.md for an AI Studio project. Installs project-level Claude Code configuration — rules, skills, settings, and optionally agents, hooks, and MCP servers — into the .claude/ directory so that all future sessions have the right guardrails and workflows.
Installs NemoClaw, launches a sandbox, and runs the first agent prompt. Use when onboarding, installing, or launching a NemoClaw sandbox for the first time. Trigger keywords - nemoclaw quickstart, install nemoclaw openclaw sandbox, nemohermes quickstart, hermes agent nemoclaw, run hermes openshell sandbox, nemoclaw prerequisites, nemoclaw supported platforms, nemoclaw hardware software, nemoclaw windows wsl2 setup, nemoclaw install windows docker desktop.