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Found 10 Skills
Create and configure Claude Code subagents for specialized task delegation. Use when defining expert AI assistants with focused responsibilities, custom prompts, and specific tool permissions.
Compose Mapbox MCP tools to produce grounded, cited location-aware responses from live data instead of training data
Start here. Introduces what NemoClaw is, what agent skills are available, and which skill to use for a given task. Use when discovering NemoClaw capabilities, choosing the right skill, or orienting in the project. Trigger keywords - skills, capabilities, what can I do, help, guide, index, overview, start here.
This skill should be used when creating custom agents for Claude Code, configuring specialized AI assistants, or when the user asks about agent creation, agent configuration, or delegating tasks to workers. Covers both file-based agents and teams delegation.
Expert in deploying and customizing a modular RAG system with MCP protocol for AI assistants
Create and configure custom OpenCode agents (primary and subagents) with specialized prompts, tools, permissions, and models. Use when the user wants to create, modify, or configure OpenCode agents, or mentions agent modes, tool permissions, or task delegation.
Twitter/X MCP server for fetching user profiles, tweets, follower events, and KOL tracking via AI assistants
Explains how OpenClaw, OpenShell, and NemoClaw form the ecosystem, NemoClaw's position in the stack, what NemoClaw adds beyond the community sandbox, and when to prefer NemoClaw versus integrating OpenShell and OpenClaw directly. Use when users ask about the relationship between OpenClaw, OpenShell, and NemoClaw, or when to use NemoClaw versus OpenShell. Trigger keywords - nemoclaw ecosystem, openclaw openshell, nemoclaw vs openshell, sandboxed openclaw, how nemoclaw works, nemoclaw sandbox lifecycle blueprint, nemoclaw overview, openclaw always-on assistants, nvidia openshell, nvidia nemotron, nemoclaw release notes, nemoclaw changelog.
Multi-agent PR and code review workflow for projects using multiple AI assistants (Claude, GitHub Copilot/Codex, Gemini Code Assist). Use when working with pull requests, code reviews, commits, or addressing review feedback. Teaches how to check all feedback sources (conversation, inline, reviews), respond to inline bot comments, create Fix Reports, and coordinate between agents that use different comment formats. Critical for ensuring no feedback is missed from external review bots.
Use FuzzingLabs MCP Security Hub to integrate offensive security tools (Nmap, Nuclei, SQLMap, Ghidra, etc.) with AI assistants via Docker-based MCP servers