Agent Node

The Agent node is the most fundamental node type in the DevAll platform, used to invoke Large Language Models (LLMs) for text generation, conversation, reasoning, and other tasks. It supports multiple model providers (OpenAI, Gemini, etc.) and can be configured with advanced features like tool calling, chain-of-thought, and memory.

Configuration

Field	Type	Required	Default	Description
`provider`	string	Yes	`openai`	Model provider name, e.g., `openai`, `gemini`
`name`	string	Yes	-	Model name, e.g., `gpt-4o`, `gemini-2.0-flash-001`
`role`	text	No	-	System prompt
`base_url`	string	No	Provider default	API endpoint URL, supports `${VAR}` placeholders
`api_key`	string	No	-	API key, recommend using environment variable `${API_KEY}`
`params`	dict	No	`{}`	Model call parameters (temperature, top_p, etc.)
`tooling`	object	No	-	Tool calling configuration, see Tooling Module
`thinking`	object	No	-	Chain-of-thought configuration, e.g., chain-of-thought, reflection
`memories`	list	No	`[]`	Memory binding configuration, see Memory Module
`skills`	object	No	-	Agent Skills discovery and built-in skill activation/file-read tools
`retry`	object	No	-	Automatic retry strategy configuration

Retry Strategy Configuration (retry)

Field	Type	Default	Description
`enabled`	bool	`true`	Whether to enable automatic retry
`max_attempts`	int	`5`	Maximum number of attempts (including first attempt)
`min_wait_seconds`	float	`1.0`	Minimum backoff wait time
`max_wait_seconds`	float	`6.0`	Maximum backoff wait time
`retry_on_status_codes`	list[int]	`[408,409,425,429,500,502,503,504]`	HTTP status codes that trigger retry

Agent Skills Configuration (skills)

Field	Type	Default	Description
`enabled`	bool	`false`	Enable Agent Skills discovery for this node
`allow`	list[object]	`[]`	Optional allowlist of skills from the project-level `.agents/skills/` directory; each entry uses `name`

Agent Skills Notes

Skills are discovered from the fixed project-level .agents/skills/ directory.
The runtime exposes two built-in skill tools: activate_skill and read_skill_file.
read_skill_file only works after the relevant skill has been activated.
Skill SKILL.md frontmatter may include optional allowed-tools using the Agent Skills spec format, for example allowed-tools: execute_code.
If a selected skill requires tools that are not bound on the node, that skill is skipped at runtime.
If no compatible skills remain, the agent is explicitly instructed not to claim skill usage.

When to Use

Text generation: Writing, translation, summarization, Q&A, etc.
Intelligent conversation: Multi-turn dialogue, customer service bots
Tool calling: Enable the model to call external APIs or execute functions
Complex reasoning: Use with thinking configuration for deep thought
Knowledge retrieval: Use with memories to implement RAG patterns

Examples

Basic Configuration

nodes:
  - id: Writer
    type: agent
    config:
      provider: openai
      base_url: ${BASE_URL}
      api_key: ${API_KEY}
      name: gpt-4o
      role: |
        You are a professional technical documentation writer. Please answer questions in clear and concise language.
      params:
        temperature: 0.7
        max_tokens: 2000

Configuring Tool Calling

nodes:
  - id: Assistant
    type: agent
    config:
      provider: openai
      name: gpt-4o
      api_key: ${API_KEY}
      tooling:
        type: function  # Tool type: function, mcp_remote, mcp_local
        config:
          tools:  # List of function tools from functions/function_calling/ directory
            - name: describe_available_files
            - name: load_file
          timeout: 20  # Optional: execution timeout (seconds)

Configuring MCP Tools (Remote HTTP)

nodes:
  - id: MCP Agent
    type: agent
    config:
      provider: openai
      name: gpt-4o
      api_key: ${API_KEY}
      tooling:
        type: mcp_remote
        config:
          server: http://localhost:8080/mcp  # MCP server endpoint
          headers:  # Optional: custom request headers
            Authorization: Bearer ${MCP_TOKEN}
          timeout: 30  # Optional: request timeout (seconds)

Configuring MCP Tools (Local stdio)

nodes:
  - id: Local MCP Agent
    type: agent
    config:
      provider: openai
      name: gpt-4o
      api_key: ${API_KEY}
      tooling:
        type: mcp_local
        config:
          command: uvx  # Launch command
          args: ["mcp-server-sqlite", "--db-path", "data.db"]
          cwd: ${WORKSPACE}  # Optional, usually not needed
          env:  # Optional, usually not needed
            DEBUG: "true"
          startup_timeout: 10  # Optional: startup timeout (seconds)

Gemini Multimodal Configuration

nodes:
  - id: Vision Agent
    type: agent
    config:
      provider: gemini
      base_url: https://generativelanguage.googleapis.com
      api_key: ${GEMINI_API_KEY}
      name: gemini-2.5-flash-image
      role: You need to generate corresponding image content based on user input.

Configuring Retry Strategy

nodes:
  - id: Robust Agent
    type: agent
    config:
      provider: openai
      name: gpt-4o
      api_key: ${API_KEY}
      retry:  # Retry is enabled by default, you can customize it
        enabled: true
        max_attempts: 3
        min_wait_seconds: 2.0
        max_wait_seconds: 10.0

Configuring Agent Skills

nodes:
  - id: Skilled Agent
    type: agent
    config:
      provider: openai
      name: gpt-4o
      api_key: ${API_KEY}
      skills:
        enabled: true
        allow:
          - name: python-scratchpad
          - name: rest-api-caller

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