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

cd tubecli
pip install -e .
tubecli init

3. CLI Commands

Initialize

tubecli init  # Creates data dirs, installs default skills, creates default agent

Agents

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

tubecli skill list
tubecli skill show "AI Summarizer"
tubecli skill run "AI Summarizer" --input "Text to summarize"
tubecli skill run "Batch Command Runner"

Workflows

tubecli workflow list
tubecli workflow run workflow.json --input "input text"

API Server

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

{
  "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

{
  "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:

{
  "name": "My Custom Skill",
  "description": "What it does",
  "skill_type": "Skill",
  "workflow_data": {
    "nodes": [...],
    "connections": [...]
  }
}

9. Common Workflow Patterns

Pattern: Input → AI → Output

{
  "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

{
  "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"}
  ]
}