prompt-engineering
Use this skill when you writing commands, hooks, skills for Agent, or prompts for sub agents or any other LLM interaction, including optimizing prompts, improving LLM outputs, or designing production prompt templates.
multi-llm-consult
Consult external LLMs (Gemini, OpenAI/Codex, Qwen) for second opinions, alternative plans, independent reviews, or delegated tasks. Use when a user asks for another model's perspective, wants to compare answers, or requests delegating a subtask to Gemini/Codex/Qwen.
repo-clipboard
Snapshot the current directory into pseudo-XML for LLM context. Use when you need to share a repo (or a sub-tree) with Codex/LLMs, especially for code review/debugging, generating an agent-friendly “repo snapshot”, or piping context into tools like `llm` (see skill $llm-cli). Supports `.gitignore`-aware file discovery, common ignore patterns, extension filtering, regex include/exclude, optional file-list printing, line-range snippets, and writes `/tmp/repo_clipboard.{stdout,stderr}` for reuse.
mcp-builder
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
mcp-builder
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
llamafile
When setting up local LLM inference without cloud APIs. When running GGUF models locally. When needing OpenAI-compatible API from a local model. When building offline/air-gapped AI tools. When troubleshooting local LLM server connections.
litellm
When calling LLM APIs from Python code. When connecting to llamafile or local LLM servers. When switching between OpenAI/Anthropic/local providers. When implementing retry/fallback logic for LLM calls. When code imports litellm or uses completion() patterns.
llm-cli
Process textual and multimedia files with various LLM providers using the llm CLI. Supports both non-interactive and interactive modes with model selection, config persistence, and file input handling.
openai
OpenAI API via curl. Use this skill for GPT chat completions, DALL-E image generation, Whisper audio transcription, embeddings, and text-to-speech.
