TubeCLI System Guide
Complete guide for AI agents to understand, install, and operate TubeCLI
Best use case
TubeCLI System Guide is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Complete guide for AI agents to understand, install, and operate TubeCLI
Teams using TubeCLI System Guide should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/skills/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How TubeCLI System Guide Compares
| Feature / Agent | TubeCLI System Guide | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Complete guide for AI agents to understand, install, and operate TubeCLI
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# TubeCLI — AI Agent Operating Guide
## 1. System Overview
TubeCLI is a headless CLI system for managing AI agents, skills (workflow templates), and workflows.
AI agents can use this system via CLI commands or REST API.
### Architecture
```
tubecli (Click CLI)
├── agent — Manage AI agents (create, list, delete)
├── skill — Manage & run skills (workflow templates)
├── workflow — Run workflow JSON files
├── api — Start REST API server
└── init — Initialize workspace
```
### Key Concepts
- **Agent**: An AI entity with name, description, system prompt, persona, and assigned skills
- **Skill**: A reusable workflow template (DAG of connected nodes)
- **Workflow**: A directed acyclic graph (DAG) of nodes connected by ports
- **Node**: An execution unit with typed input/output ports (text, json, file, any)
## 2. Installation
```bash
cd tubecli
pip install -e .
tubecli init
```
## 3. CLI Commands
### Initialize
```bash
tubecli init # Creates data dirs, installs default skills, creates default agent
```
### Agents
```bash
tubecli agent create "Agent Name" --description "desc" --model "qwen:latest"
tubecli agent list
tubecli agent show <agent_id_or_name>
tubecli agent delete <agent_id>
```
### Skills
```bash
tubecli skill list
tubecli skill show "AI Summarizer"
tubecli skill run "AI Summarizer" --input "Text to summarize"
tubecli skill run "Batch Command Runner"
```
### Workflows
```bash
tubecli workflow list
tubecli workflow run workflow.json --input "input text"
```
### API Server
```bash
tubecli api start --port 5295
tubecli api status
```
## 4. REST API Reference
Base URL: `http://localhost:5295`
| Method | Endpoint | Description |
|--------|----------|-------------|
| GET | /api/v1/health | Health check |
| GET | /api/v1/agents | List agents |
| POST | /api/v1/agents | Create agent |
| GET | /api/v1/agents/{id} | Get agent |
| PUT | /api/v1/agents/{id} | Update agent |
| DELETE | /api/v1/agents/{id} | Delete agent |
| GET | /api/v1/skills | List skills |
| POST | /api/v1/skills | Create skill |
| DELETE | /api/v1/skills/{id} | Delete skill |
| POST | /api/v1/workflows/run | Execute workflow |
| GET | /api/v1/nodes | List node types |
## 5. Workflow JSON Format
```json
{
"name": "My Workflow",
"nodes": [
{"id": "input1", "type": "text_input", "config": {"text": "Hello"}},
{"id": "ai1", "type": "ai_node", "config": {"model": "qwen:latest"}},
{"id": "out1", "type": "output", "config": {"print": true}}
],
"connections": [
{"from_node_id": "input1", "from_port_id": "content", "to_node_id": "ai1", "to_port_id": "prompt"},
{"from_node_id": "ai1", "from_port_id": "response", "to_node_id": "out1", "to_port_id": "data"}
]
}
```
## 6. Available Node Types
| Type | Name | Inputs | Outputs | Description |
|------|------|--------|---------|-------------|
| text_input | 📝 Text Input | — | content, lines | Static text |
| loop | 🔄 Loop | items | current_item, index, total | Iterate list |
| python_code | 🐍 Python Code | text_input, json_input | result | Execute Python |
| api_request | 🌐 API Request | url, body | response, status_code | HTTP request |
| run_command | 💻 Run Command | command | stdout, exit_code | Shell command |
| ai_node | 🧠 AI Inference | prompt, context | response | AI model call |
| output | 📤 Output | data | file_path | Display/save results |
## 7. Agent JSON Schema
```json
{
"id": "uuid",
"name": "Agent Name",
"description": "What this agent does",
"system_prompt": "You are...",
"allowed_skills": ["skill_id_1", "skill_id_2"],
"model": "qwen:latest",
"persona": {},
"routine": {},
"cloud_api_keys": {"gemini": "", "openai": "", "claude": "", "deepseek": ""}
}
```
## 8. Creating Custom Skills
To create a custom skill, POST to `/api/v1/skills` or use the skill manager:
```json
{
"name": "My Custom Skill",
"description": "What it does",
"skill_type": "Skill",
"workflow_data": {
"nodes": [...],
"connections": [...]
}
}
```
## 9. Common Workflow Patterns
### Pattern: Input → AI → Output
```json
{
"nodes": [
{"id": "in", "type": "text_input", "config": {"text": "..."}},
{"id": "ai", "type": "ai_node", "config": {}},
{"id": "out", "type": "output", "config": {}}
],
"connections": [
{"from_node_id": "in", "from_port_id": "content", "to_node_id": "ai", "to_port_id": "prompt"},
{"from_node_id": "ai", "from_port_id": "response", "to_node_id": "out", "to_port_id": "data"}
]
}
```
### Pattern: Loop → Command → Output
```json
{
"nodes": [
{"id": "list", "type": "text_input", "config": {"text": "cmd1\ncmd2"}},
{"id": "loop", "type": "loop", "config": {}},
{"id": "exec", "type": "run_command", "config": {}},
{"id": "out", "type": "output", "config": {}}
],
"connections": [
{"from_node_id": "list", "from_port_id": "lines", "to_node_id": "loop", "to_port_id": "items"},
{"from_node_id": "loop", "from_port_id": "current_item", "to_node_id": "exec", "to_port_id": "command"},
{"from_node_id": "exec", "from_port_id": "stdout", "to_node_id": "out", "to_port_id": "data"}
]
}
```Related Skills
Ollama Local Model Manager — AI Skill Guide
## Extension: ollama
Multi-Agent Orchestration — AI Skill Guide
## Extension: multi_agents
Cloud API Management — AI Skill Guide
## Extension: cloud_api
Universal Tracker
Cross-platform background monitor to auto-detect new videos/posts (YouTube, Douyin, Website) and run team workflows.
File Manager
Quản lý file và folder trên máy tính
SKILL.md — Video Downloader Extension
## Mô tả
calendar_manager
Manage Google Calendar — create, list, update, delete events with recurring & reminders
Browser Automation
Quản lý browser profiles anti-detect, mở/đóng trình duyệt, tự động hóa web
auth_manager
Manage OAuth credentials & tokens for Google, Facebook, TikTok
design-system
Use this skill to generate or audit design systems, check visual consistency, and review PRs that touch styling.
memory-systems
Design short-term, long-term, and graph-based memory architectures. Use when building agents that must persist across sessions, needing to maintain entity consistency across conversations, or implementing reasoning over accumulated knowledge.
hig-components-system
Apple HIG guidance for system experience components: widgets, live activities, notifications, complications, home screen quick actions, top shelf, watch faces, app clips, and app shortcuts.