> ## Documentation Index > Fetch the complete documentation index at: https://docs.charmos.io/llms.txt > Use this file to discover all available pages before exploring further. # Manifest Reference `charm.yaml` is the manifest that tells Charm how to display, run, price, and publish an agent. ## Annotated Reference This is a fully annotated example to understand specific capabilities or customization options. ```yaml theme={"theme":{"light":"min-light","dark":"min-dark"}} # ================================================================== # 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: : # -------------------------------------------------------------- # [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 ``` ### Field Reference Table | Section | Field | Type | Description | | --------- | ---------------------- | ------- | ------------------------------------------------------------------------- | | Persona | name | String | Public display name of the agent. | | | version | String | The semantic version of the agent (e.g., 1.0.0). | | | description | String | Short tagline for search results and cards. | | | assets.icon | URL | 512x512px PNG/JPG image. | | Pricing | model | Enum | free, subscription, one\_time. | | | amount | Number | Price in USD. Ignored if free. | | | billing\_period | Enum | monthly, annual (for subscription). | | | trial.enabled | Boolean | Whether trial is offered. | | | trial.days | Integer | Number of trial days. | | Interface | input | Schema | Standard JSON Schema defining user inputs. | | | ui | Object | Maps input keys to UI widgets (e.g. textarea, file). | | | state | Schema | Optional JSON Schema defining persistent state. | | Runtime | adapter.type | Enum | crewai, langchain, langgraph, custom, openclaw. | | | entry\_point | String | Python path (module:obj). Optional for openclaw. | | | environment\_variables | Object | Map of 'models' and 'tools' requiring Env keys (e.g., OPENAI\_API\_KEY). | | | config | Object | Engine-specific configuration (e.g. OpenClaw system\_prompt, model). | | | skills | List | List of MCP Skills to mount. | | | custom\_image | String | Custom Docker image URI for the runtime environment. | | | memory | Object | Configuration for persistent memory and state storage (e.g., provider). | | | telemetry | List | List of telemetry exporter names to enable. | | | mode | Enum | standard (Default), full. Selects the container environment (Deprecated). | | Auth | providers | List | List of OAuth providers. | | Policies | max\_steps | Integer | Maximum execution steps to prevent infinite loops. |