ai

Full command reference for Open Interpreter, a terminal AI coding agent: install and launch, --local local models, -y auto-accept, --os OS control, --api_base custom endpoint, resume --last session restore and /model interactive commands, all matched to official docs.

Full command reference for GPT Engineer gpte and gpt-engineer CLI: create projects, improve code with -i, --model selection, --steps workflows, and --temperature, all matched to official docs.

Full command reference for Mentat CLI: pass files or dirs as context, --exclude to drop paths, --auto-context retrieval, --model switch, --mcp-server for tools, and /include interactive commands, all matched to official docs.

Full command reference for CrewAI crewai CLI: create crew, run, train, flow workflows, tool management, and install, all matched to official docs.

Full command reference for Phidata phi CLI: init, auth, config, ws create/up/down workspace management, start/stop resource deploy, all matched to official docs.

Full command reference for Tabby tabby CLI: serve to start, --model/--device/--port flags, download models, scheduler to trigger indexing, and OpenAI-compatible API calls, all matched to official docs.

Full command reference for Open WebUI open-webui CLI: serve to start, --port and --host flags, DATA_DIR, pip install and update, Docker and K8s deploy, all matched to official docs.

Full command reference for gptme CLI: start a chat, -m model, -t tools, -y auto-confirm, -n non-interactive, --output-format json, resume, and tools/chats/models subcommands, all matched to official docs.

Full command reference for Tabnine CLI: tabnine to start, /help /model /clear /settings slash commands, -p non-interactive mode, TABNINE_TOKEN auth, and tabnine-opencode integration, all matched to official docs.

Command reference for Hermes Agent, Nous Research open-source, model-agnostic terminal AI agent: install, model & tool configuration, message gateway, and setup wizard, covering hermes model, hermes tools, hermes config set, and hermes gateway.

Command reference for Kilo Code CLI, the terminal AI coding agent sharing an engine with the IDE extensions: install, interactive & one-off tasks, and model integrations, covering kilo run, kilo --mode, kilo --auto, kilo auth, and kilo mcp.

Command reference for Pi, the earendil-works multi-model terminal coding agent: install, interactive sessions, headless mode & scripting, and session/model management, covering pi -c, pi -p, pi @file, /login, and /model.

Command reference for Kimi Code CLI, Moonshot AI terminal AI coding agent wired to Kimi models: install, interactive & single instructions, and sessions & models, covering kimi -p, kimi -C, /login, /init, and /model.

Command reference for Grok CLI, the xAI Grok Build terminal AI coding agent: install, interactive sessions, session management, headless mode, and scripting, covering grok -p, grok inspect, XAI_API_KEY, and /model.

Command reference for Warp Agent CLI, the AI coding agent built into the Warp terminal: install, core agent commands, MCP integration, and cloud agents, covering /agent, /model, /plan, /orchestrate, /mcp, and oz agent run.

Command reference for Crush, the Charmbracelet Rust single-binary terminal AI coding agent: install, sessions & modes, and configuration, covering crush --yolo, /model, and crush logs.

Command reference for Antigravity CLI (Google terminal AI coding agent, command agy): install, sessions & planning, and tools & integrations, covering agy, /model, /planning, /mcp, and /permissions.

Command reference for Plandex, the terminal planning open-source AI coding agent (alias pdx): install, plan & load, and execute & iterate, covering plandex new, plandex load, plandex tell, and OPENROUTER_API_KEY.

Model-agnostic prompt engineering techniques covering role anchoring, structured output, explicit constraints, Few-shot, Chain of Thought, self-verification, and common pitfalls, not tied to any specific tool.

Retrieval-Augmented Generation (RAG) prompt patterns covering answer-only-from-context, cite sources, handle no-answer, fuse multi-passage evidence, and flag conflicts — emphasizing traceability and hallucination control.

Autonomous-agent system-prompt patterns covering goal/role definition, tool declarations, step-by-step decision loops, guardrails & permissions, error handling, and reflection — emphasizing control and safety.

Model-agnostic text-to-image (Midjourney/Stable Diffusion/SDXL) prompt structure covering subject, style & artists, composition & lens, light & material, negative prompts, and common params.

Code-generation prompt patterns covering requirement & context handoff, language/framework/version constraints, I/O contracts, edge cases & tests, and acceptance criteria — emphasizing compilable, runnable output.

Command reference for Amazon Q Developer CLI, AWS official terminal AI coding agent: install, login, chat, one-line queries, and Agent mode, covering brew install amazon-q, q chat, q one-line queries, and /q slash commands.

Command reference for Sourcegraph Amp, the terminal AI coding agent: install, login, one-shot prompts, background execution, and thread management, covering @sourcegraph/amp, amp prompts, amp -x background tasks, and amp threads.

Command reference for LiteLLM, unified OpenAI-compatible gateway for 100+ LLMs: proxy launch, provider-prefix routing, config-file mode, and self-test, covering litellm --model, litellm --config, and litellm --test.

Command reference for vLLM, the high-performance LLM inference & serving engine: install, OpenAI-compatible server launch, host/port/API-key configuration, and quantization, covering pip install vllm, vllm serve, and --host/--port/--api-key.

Command reference for llamafile, Mozilla single-file local LLM runner: download & run, OpenAI-compatible server, GGUF loading, GPU layers, and temperature, covering ./xxx.llamafile --server, --nobrowser, -m, --ngl, --temp.

Command reference for Continue CLI (cn, open-source terminal coding agent sharing the engine with the VS Code/JetBrains extensions): install, interactive session, headless mode, login, and thread resume, covering cn, cn -p, cn login, and cn --resume.

Prompt-writing reference for DeepSeek that distinguishes the reasoning model R1 (deepseek-reasoner) from the chat model V3 (deepseek-chat), covering R1 hard rules (no system prompt, instructions in user, no few-shot, temperature 0.6) and V3 system-lock, few-shot, and JSON/function calling.

Gemini prompt engineering reference covering structured delimiters (XML/Markdown tags), long-context anchoring, internal-thinking and date/grounding clauses, native multimodal (text/image/audio/video) input, and model selection (3.5 Flash / 3.1 Pro / 2.5 Pro 1M / 2.5 Flash).

Stable Diffusion and SDXL prompt templates: six-segment structure, token weights, negative prompts, LoRA, ControlNet, CFG, steps, sampler, VRAM planning.

Kling AI video-generation prompt reference covering camera moves (push-in/pull-out/pan/tilt/dolly/orbit/crane/tracking), the one-move-per-shot rule, the six-segment prompt structure, and API params (camera_control/aspect_ratio/duration/model).

Perplexity prompt techniques covering "write questions not keywords", Focus modes (Web/Academic/Pro Search/Research/Reddit/YouTube/Writing/Math/Finance), date & source constraints, format constraints, chained follow-ups, and citations.

NotebookLM prompt techniques covering source management (PDF/URL/transcript/spreadsheet), answer-only-from-uploaded-sources with inline citations, verification prompts (find contradictions/gaps/counterpoints), and Learning Guide & Studio (study guide/infographic/audio) generation.

OpenCode TUI agent reference: launch and resume, CLI flags, agent/auth/github/mcp subcommands, serve mode, and interactive slash commands.

Goose terminal agent reference: install and auth, setup across 15+ LLM providers, MCP extensions, sessions and diagnostics via goose run/configure/doctor.

A cheat sheet for the OpenHands autonomous coding agent: launch tasks with -t, auto-approve with --yolo, resume with --resume, and manage MCP servers.

VS Code AI coding with Cline: run Cline: Ask or Cline: Refactor from the palette, reference context with @file and @folder, and switch Plan and Act modes.

Ollama command reference: run and chat, pull/push, model management, Modelfile customization, serve on port 11434 and OpenAI-compatible API endpoints.

Qwen Code CLI reference: install, auth, launch, print mode, every slash command and MCP setup for Alibaba's open-source Qwen3-Max coding agent.

Command reference for GitHub Copilot CLI (gh CLI extension): explain commands, generate shell suggestions, aliases, and config, covering gh copilot explain/suggest/alias/config and @copilot.

Full command reference for Claude Code, Anthropic terminal AI coding agent: install & auth, -p print mode and session resume, --permission-mode/--worktree, dev slash commands, MCP server management, and @ file references, all flags matching official docs.

OpenAI Codex CLI reference: install and auth, interactive mode, codex exec, sessions, sandbox and approval modes, MCP setup and Codex Cloud.

Command reference for Gemini CLI, Google open-source (Apache 2.0) terminal AI agent: install & auth, run modes and global flags, session slash commands, MCP/extension management, and GEMINI.md project memory, with a 2M context.

Cursor IDE CLI: new window (cursor -n), reuse windows (-r), diff, extensions, remote dev and cursor-agent flags.

Terminal AI pair programming with Aider: add files with /add, switch to /architect, auto git-commit every edit, and lint changes via --lint-cmd.

ChatGPT prompt templates by task: set a role, force JSON with a schema, review code, and use Few-shot examples or Chain of Thought.

Claude prompt templates for long docs (200K), code analysis, system prompts, structured output and multi-turn methods.

Midjourney prompt cheatsheet: parameters (--ar, --v, --q, --niji, --no), style keywords, camera and lighting modifiers, weight syntax and prompt skeletons.

Prompt-design patterns and templates for ChatGPT: role assignment, task framing and step breakdown, output-format constraints, few-shot examples and chain-of-thought steering — with common office, coding and writing scenarios. For turning vague asks into consistent, controllable model output.