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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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