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Found 94 Skills
Runs external LLM code reviews (OpenAI Codex or Google Gemini CLI) on uncommitted changes, branch diffs, or specific commits. Use when the user asks for a second opinion, external review, codex review, gemini review, or mentions /second-opinion.
Universal skill diagnosis and optimization tool. Detect and fix skill execution issues including context explosion, long-tail forgetting, data flow disruption, and agent coordination failures. Supports Gemini CLI for deep analysis. Triggers on "skill tuning", "tune skill", "skill diagnosis", "optimize skill", "skill debug".
Model Context Protocol (MCP) server development and tool management. Languages: Python, TypeScript. Capabilities: build MCP servers, integrate external APIs, discover/execute MCP tools, manage multi-server configs, design agent-centric tools. Actions: create, build, integrate, discover, execute, configure MCP servers/tools. Keywords: MCP, Model Context Protocol, MCP server, MCP tool, stdio transport, SSE transport, tool discovery, resource provider, prompt template, external API integration, Gemini CLI MCP, Claude MCP, agent tools, tool execution, server config. Use when: building MCP servers, integrating external APIs as MCP tools, discovering available MCP tools, executing MCP capabilities, configuring multi-server setups, designing tools for AI agents.
Gemini CLI consultation workflow for coding agents. Use when technical tasks need Gemini consultation for decisions, planning, debugging, problem-solving, or pre-implementation guidance.
Delegate a sub-task to Gemini CLI via the Agent Client Protocol (ACP). Use this skill whenever you want to hand off work to Gemini — large-context summarization, Google Search grounding, tasks that exceed Claude's context window, or anything where Gemini's 1M-token window or real-time search gives an advantage. Also invoke when the user asks you to "ask Gemini", "check with Gemini", or "run this through Gemini". The script handles subprocess lifecycle and ACP session setup; you just provide the prompt and read stdout.
Run Gemini CLI for AI-powered tasks, code understanding, file operations, and automation. Free tier with Google OAuth (included in Gemini Advanced). Use for fast generation, bulk content, debugging, and research. Preferred for load balancing sub-agent work (35% weight).
Generate marketing demo HTML for any repository using a hook+demo pipeline. This skill scans source code into <code="..."> blocks, creates plan outlines, generates hook/demo HTML, and optionally merges them. Use when you need one-click demo generation for arbitrary repos with Gemini CLI (`gemini -m`), including selectable hook templates (`text`, `shorts`, `4methods`).
Use when the user wants to invoke Google Gemini CLI for reasoning tasks, research, and AI assistance. Trigger phrases: "use gemini", "ask gemini", "run gemini", "call gemini", "gemini cli", "Google AI", "Gemini reasoning", or when users request Google's AI models, research with web search, or want to continue a previous Gemini session.
Interact with Google's Gemini model via CLI. Use when needing a second opinion from another LLM, cross-validation, or leveraging Gemini's Google Search grounding. Supports multi-turn conversations with session management.
Optimize token usage when delegating to Gemini CLI. Covers token caching, batch queries, model selection (Flash vs Pro), and cost tracking. Use when planning bulk Gemini operations.
Use Gemini CLI to simplify the current pull request by safely reducing unnecessary scope, complexity, and noise while preserving the intended outcome.
Setup and workflow for using sqry semantic code search as an MCP server with Gemini CLI. Covers installation, MCP configuration via settings.json, context file behavior, and recommended patterns. Install this skill to give Gemini CLI access to sqry's 34 AST-based code analysis tools.