Manifest Reference

# ==================================================================
# Charm Agent Manifest (Annotated Reference)
# ==================================================================

version: "{manifest_version}"  # [System] The UAC Spec version (Do not change manually).

# ------------------------------------------------------------------
# 1. Identity & Store Metadata
# ------------------------------------------------------------------
persona:
  name: "My Charm Agent" # Display Project Name (Max 50 chars)
  version: "0.1.0" # [Agent] Your Agent's Semantic Version. Update this when publishing updates.
  description: "A short description of this agent." # Tagline (Card view, Max 100 chars)
  
  # Full description supports Markdown. Used for the Info Page.
  full_description: |
    # My Charm Agent
    ...
  # Describe usage, available capabilities, and expected deliverables.
    
  authors: ["Brand, Company, or Individual Name"]
  tags: ["research", "productivity"] # We use tags to categorize agents for users, so please make sure your first tag is one of Productivity, Developer, Creative, Learning, Lifestyle, Search & News, or Others.
  license: "MIT"
  
  # Assets for the Storefront
  assets:
    icon: "https://your-site.com/assets/icon.png" # 512x512 Square
    banner: "https://your-site.com/assets/banner.png"  # 1200x600 Wide

pricing:
  model: "free"  # Options: free, subscription, one_time.
  amount: 0      # Price in USD. Ignored when model is 'free'.
  # billing_period: "monthly" # Options: monthly, annual (for subscription)
  # trial:
  #   enabled: true
  #   days: 7

# ------------------------------------------------------------------
# 2. UI Generation
# ------------------------------------------------------------------
# Defines the input form shown to users.
# It uses standard JSON Schema.
interface:
  input:
    type: "object"
    required: ["topic"] # Mandatory fields
    properties:
      # Example 1: Simple Text Input
      topic:
        type: "string"
        title: "Research Topic"
        default: "AI Agents"
      
      # Example 2: Large Text Area
      details:
        type: "string"
        title: "Extra Details"
        description: "Paste any background info here."
      
      # Example 3: File Upload
      # The Runner will download the file and inject the filename into this variable.
      document:
        type: "string"
        title: "Upload Document"

      # Example 4: Number Input
      depth:
        type: "integer"
        title: "Search Depth"
        default: 3
        minimum: 1
        maximum: 5

  # Maps input fields to frontend UI components
  ui:
    details: { "ui:widget": "textarea" }
    document: { "ui:widget": "file" }

  output:
    type: "object"
    description: "The structure of the final result."

  # Optional: For agents that persist state across runs
  state:
    format: "json"
    schema:
      type: "object"
      properties:
        history:
          type: "array"
      additionalProperties: false

# ------------------------------------------------------------------
# 3. Runtime Configuration
# ------------------------------------------------------------------
runtime:
  adapter:
    # - crewai / langchain / langgraph : Standard Python Frameworks
    # - openclaw : Configuration-driven Agent
    # - custom : Pure Python functions
    type: "crewai"
    
    # --------------------------------------------------------------
    # ENTRY POINT: Where is your agent object?
    # Format: <python_module_path>:<variable_or_function_name>
    # --------------------------------------------------------------
    # [Case A] For Frameworks (CrewAI, LangChain): Point to the agent instance.
    entry_point: "src.main:my_crew"
    
    # [Case B] For Custom (Pure Python): Point to a function or class instance.
    entry_point: "src.my_script:run_pipeline"

    # [Case C] For OpenClaw: Optional (uses default host if empty)
    entry_point: ""
    
    # --------------------------------------------------------------
    # SECURE ENV VARS: List keys your agent needs.
    # DO NOT put values here. The Runner injects them securely.
    # --------------------------------------------------------------
    environment_variables:
      models:
        - "OPENAI_API_KEY"
      tools:
        - "SERPER_API_KEY"

  # --------------------------------------------------------------
  # ENGINE CONFIG: For OpenClaw or specific engines
  # --------------------------------------------------------------
  config:
    system_prompt: "You are an expert researcher."
    model: "gpt-4o"
    temperature: 0.0
    auto_install_dependencies: true

  # --------------------------------------------------------------
  # SKILLS & MCP TOOLS
  # --------------------------------------------------------------
  skills:
    
    # [Source: Git] 
    - name: "research-flow"
      source: "git:https://github.com/openclaw/skill-researcher"
      version: "main" # Or Commit Hash / Tag (If you want to pin the version)

    # [Source: Zip] 
    - name: "finance-analyst"
      source: "https://clawhub.ai/download/skills/finance-v1.2.0.zip"

    # [Source: NPM] 
    - name: "google-search"
      source: "npm:@modelcontextprotocol/server-google-search"

    # [Source: PyPI] 
    - name: "local-time"
      source: "pip:mcp-server-time"
  
  # --------------------------------------------------------------
  # Memory & State Storage (Optional)
  # --------------------------------------------------------------
  memory:
    provider: "local" # Options: local, redis, postgres (Requires custom memory plugin)
    
  # --------------------------------------------------------------
  # Observability (Optional)
  # --------------------------------------------------------------
  telemetry:
    - "datadog" # Enable custom telemetry exporters
  
  # --------------------------------------------------------------
  # Base Image
  # --------------------------------------------------------------
   # Override standard images with your own custom Docker image
  # custom_image: "ghcr.io/your-org/my-agent-image:latest"

  # --------------------------------------------------------------
  # Execution Mode
  # --------------------------------------------------------------
   # "serverless": Runs once and shuts down. Perfect for one-time tasks, async workflows, or heavy batch processing.
   # "interactive": Built for continuous dialogue. Keeps context alive for seamless, back-and-forth interactions.
   # "daemon": 24/7 always-on. Ideal for monitoring, event listeners, or continuous background services.
  lifecycle: "serverless"

# ------------------------------------------------------------------
# 4. Authentication
# ------------------------------------------------------------------
# Declare if your agent needs user's OAuth tokens.
# NOTE: Use the official scope strings defined by the provider.
auth:
  providers:
    # [OAuth: Google]
    - name: "google"
      scopes: 
        - "https://www.googleapis.com/auth/calendar.readonly"
        - "https://www.googleapis.com/auth/gmail.send"

    # [OAuth: GitHub]
    - name: "github"
      scopes: 
        - "repo"
        - "read:user"

# ------------------------------------------------------------------
# 5. Governance (Policies)
# ------------------------------------------------------------------
policies:
  allow_internet_access: true
  max_steps: 20
  # Optional: Override serverless run timeout for this agent (seconds).
  # execution_timeout_seconds: 600