omnigent-knowledge

Omnigent Knowledge Base

What is Omnigent?

Agent plane is a server that hosts, manages, and executes agents via an OpenResponses-compatible API. Users create agent directories (also called agent images) that contain configuration, instructions, skills, and tools. The server loads these directories and serves them via HTTP.

Agent Directory Layout

my-agent/
├── config.yaml          # REQUIRED — agent spec
├── AGENTS.md            # Recommended — instructions/personality
├── skills/              # Optional — load-on-demand skills
│   └── <dir>/           # Free-form; skill name comes from SKILL.md
│       └── SKILL.md
├── tools/               # Optional — packaged tools
│   ├── python/          # Local Python tools (auto-discovered *.py)
│   ├── typescript/      # Local TypeScript tools (auto-discovered *.ts)
│   └── mcp/             # MCP server declarations (*.yaml)
└── agents/              # Optional — sub-agent directories (recursive)
    └── <dir>/           # Free-form; sub-agent name comes from config.yaml
        ├── config.yaml
        └── ...

config.yaml Reference

The only required file. All fields except spec_version are optional.

spec_version: 1               # REQUIRED, must be 1

name: my-agent                # Display name
description: Does X and Y.    # One-line summary

# Instructions — path to a file or inline text.
# Default: looks for AGENTS.md in the agent directory.
instructions: AGENTS.md

executor:
  # REQUIRED area. type must be one of: claude_sdk | agents_sdk | omnigent.
  # There is NO `llm` executor type.
  type: claude_sdk     # Anthropic Claude SDK, in-process (simplest)
  # type: agents_sdk   — OpenAI Agents SDK, in-process
  # type: omnigent     — subprocess harness; requires config.harness below

  # Only for type: omnigent — pick the harness that runs the loop.
  # One of: claude-native | claude-sdk | codex-native | codex |
  #         openai-agents | open-responses | pi
  # config:
  #   harness: claude-native
  #   permission_mode: bypassPermissions   # claude-native headless
  #   yolo: true                           # codex-native headless

  # Model is OPTIONAL — omit to use the configured provider's default.
  # Pin one directly on the executor when needed:
  # model: anthropic/claude-sonnet-4-20250514   # LiteLLM provider/model
  # model: databricks-claude-opus-4-7           # or a serving-endpoint name
  # connection:                                 # provider credentials
  #   api_key: ${ANTHROPIC_API_KEY}
  # auth:                                        # or Databricks profile auth
  #   type: databricks
  #   profile: oss

  timeout: 3600        # Task deadline in seconds (default: 3600)
  max_iterations: 1000 # Max LLM calls per task (default: 1000)

# os_env — grant filesystem/shell access (harness agents). Exposes
# sys_os_read / sys_os_write / sys_os_edit / sys_os_shell.
os_env:
  type: caller_process
  cwd: .
  sandbox:
    type: none         # or linux_bwrap / darwin_seatbelt to sandbox

# guardrails — runtime policy gates (optional).
guardrails:
  ask_timeout: 86400   # seconds to wait on an approval prompt
  policies:
    blast_radius:
      type: function
      function:
        path: omnigent.inner.nessie.policies.blast_radius

interaction:
  conversational: true   # Maintain turn history (default: true)
  modalities:
    input: [text, image, file]   # default: [text]
    output: [text]               # default: [text]

tools:
  # Sub-agents this agent can spawn (declared names of agents/ sub-agents)
  agents:
    - researcher
    - summarizer

  # Built-in tools — string name or dict with config
  builtins:
    - web_search                 # auto-detects backend based on model provider
    - terminal_run               # persistent bash shell scoped to the conversation
    - upload_file
    - search_conversations

  timeout: 60          # Default tool timeout in seconds

params:                # Arbitrary key-value (readable by skills/tools)
  max_results: 10