create-agent

name	create-agent
description	Help users create and configure openma managed agents through conversation. Trigger when users say "create an agent", "I need an agent that...", "set up an agent for", "build me a bot", or describe a task to automate. Also trigger for "Create with AI" from Dashboard. Also use when users ask about the openma platform, what it can do, how to use the CLI, or how to configure resources.

openma Agent Creator

What is openma?

openma is an open-source platform for building, deploying, and managing AI agents. Think of it as a managed runtime — you define an agent (model + system prompt + tools), the platform handles sandboxed execution, credential management, and session state.

What you can do with it:

• Build agents for any task: coding, research, data analysis, customer support, automation
• Run agents in sandboxes — each session gets an isolated container with file system, shell, and network
• Connect external services via MCP servers (GitHub, Slack, Linear, Notion, etc.) with OAuth
• Use any LLM — Anthropic, OpenAI, DeepSeek, or any OpenAI-compatible provider
• Install community skills from ClawHub to extend agent capabilities
• Manage credentials securely in vaults — agents get scoped access, secrets never leak
• Collaborate — multi-user workspace with API key access for CLI/SDK integration

Creating an Agent

Flow

1. Understand the goal — ask what the agent should do. If vague, one question: "What's the main task?" Two rounds max, then build.

2. Pick the model — check /v1/model_cards first. Defaults:

   • Complex/coding: claude-opus-4-6
   • General (default): claude-sonnet-4-6
   • Simple/fast: claude-haiku-4-5-20251001
   • OpenAI: gpt-4o, o3

3. Write system prompt — specific, actionable, bounded. Not generic.

4. Select tools — default agent_toolset_20260401 (file ops, bash, web) covers most cases.

5. Create:

   POST /v1/agents
   { "name", "model", "system", "tools": [{"type":"agent_toolset_20260401"}] }
   

6. Next steps — offer to create session, configure skills, set up model card.

Platform Quick Ref

Agents need a session to run. Sessions need an environment (sandbox).

Resource	What it is
Agent	Model + system prompt + tools config
Session	A conversation with an agent in a sandbox
Environment	Sandbox runtime (default works for most)
Model Card	API key + provider config for an LLM
Vault	Secure credential storage for MCP/CLI secrets
Skill	SKILL.md that gives agents domain expertise
API Key	Programmatic access token for CLI/SDK

oma agents create <name>                    # create agent
oma sessions create --agent <id> --env <id> # start session
oma sessions message <id> <text>            # send message
oma models create --name <n> --model-id <id> --api-key <key>
oma keys create                             # generate API key
oma skills install <slug>                   # install from ClawHub
oma --help                                  # full command list

Model card providers: ant, oai, ant-compatible, oai-compatible.