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Found 94 Skills
Comprehensive guide for using Codex CLI (OpenAI) and Claude Code CLI (Anthropic) - AI-powered coding agents. Use when orchestrating CLI commands, automating tasks, configuring agents, or troubleshooting issues.
Install and configure ToolUniverse with MCP integration for any AI coding client (Cursor, Claude Desktop, Windsurf, VS Code, Codex, Gemini CLI, Trae, Cline, Antigravity, OpenCode, etc.). Covers uv/uvx setup, MCP configuration, API key walkthrough, skill installation, and upgrading. Use when setting up ToolUniverse, configuring MCP servers, troubleshooting installation issues, upgrading versions, or when user mentions installing ToolUniverse or setting up scientific tools.
A software security skill that integrates with Project CodeGuard to help AI coding agents write secure code and prevent common vulnerabilities. Use this skill when writing, reviewing, or modifying code to ensure secure-by-default practices are followed.
Audit and prune bloated CLAUDE.md or AGENTS.md context files using evidence-based criteria from research on what actually helps coding agents. Use when a user asks to trim, audit, review, or improve their CLAUDE.md, AGENTS.md, or any repository context file for AI coding agents.
Run OpenAI's Codex CLI agent in non-interactive mode using `codex exec`. Use when delegating coding tasks to Codex, running Codex in scripts/automation, or when needing a second agent to work on a task in parallel.
Setup universal code quality standards in your project. Use when the user wants to generate coding standards files (CLAUDE.md, AGENTS.md, GEMINI.md, etc.) or mentions 'code standards', 'code review setup', or similar intent in any language.
Search and analyze AI coding assistant session history using Terraphim. Find past conversations, discover patterns, and learn from previous work. Supports Claude Code, Cursor, Aider, and other AI coding assistants.
Creates and reviews CLAUDE.md configuration files for Claude Code. Applies HumanLayer guidelines including instruction budgets (~50 user-level, ~100 project-level), WHAT/WHY/HOW framework, and progressive disclosure. Identifies anti-patterns like using Claude as a linter for style rules.
Audit and optimise context window usage for AI coding tools (Claude Code, OpenCode, etc.). Estimates token breakdown, identifies waste (duplicate skills, overlapping rules, bloated instruction files, dirty git status, MCP server overhead), and provides actionable recommendations with projected savings. Use when the user says "context checkup", "reduce context", "check context", "context audit", "how big is my context", or when sessions feel sluggish.
Set up or update the agent-first engineering harness for any repository. Implements the complete scaffolding that makes AI coding agents effective: knowledge maps (AGENTS.md as a concise TOC), structured documentation, architecture boundaries, enforcement rules (.harness/*.yml specs), quality scoring, and process patterns for agent-driven development. Use this skill whenever someone wants to make a repo agent-ready, set up AGENTS.md or docs/ structure, define domain boundaries or golden principles, generate .harness/ configuration, audit agent readiness, or update an existing harness. Also trigger when a user reports problems with agent effectiveness, context management, or architectural drift — these are symptoms of a missing or stale harness. Trigger on: "harness this repo", "set up harness", "agent-first setup", "make this agent-ready", "update the harness", "assess agent readiness", "set up AGENTS.md", "organize for agents", or any discussion about structuring a codebase for AI agent workflows.
Describes the agent skills shipped with NemoClaw and how to access them by cloning the repository. Use when users ask about AI agent support, coding assistant integration, or the .agents/skills/ directory. Trigger keywords - nemoclaw agent skills, ai coding assistant, cursor, claude code, copilot.
Methodology for effective AI-assisted software development. Use when helping users build software with AI coding assistants, debugging AI-generated code, planning features for AI implementation, managing version control in AI workflows, or when users mention "vibe coding," Cursor, Windsurf, or similar AI coding tools. Provides strategies for planning, testing, debugging, and iterating on code written with LLM assistance.