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Detect Python agent frameworks from code imports and map them to Omnigent executor types. Load when the user has existing agent code to integrate.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Run the Omnigent server as a Docker compose stack (server + Postgres) on any Docker host — your laptop, a VPS, EC2 by hand, or as the base layer of any container-platform deploy. Invoke when the user wants to build the image, bring up the compose stack, debug the stack on a host they already have, or extend the stack for a new platform.
Run independent subtasks in parallel — one git worktree and one implementation sub-agent per task, each opening its own PR — then cross-review every PR. polly never merges; the human does.
Patterns and templates for generating valid Omnigent agent directories. Load when ready to create files.
Deep reference on Omnigent config format, executor types, skill/tool structure, and conventions. Load when you need to look up how the platform works.
Spin up a live local Omnigent server and exercise the Antigravity (Gemini) SDK harness end-to-end — build antigravity agents, run real turns, smoke-test, and bug-bash. Load when developing, testing, or debugging the antigravity harness (omnigent/inner/antigravity_executor.py, antigravity_harness.py, omnigent/onboarding/antigravity_auth.py) or its auth / model / tool-bridge behavior.
Spin up a live local Omnigent server and exercise the Cursor SDK harness end-to-end — build cursor agents, run real turns, smoke-test, and bug-bash. Load when developing, testing, or debugging the cursor harness (omnigent/inner/cursor_executor.py, cursor_harness.py, cursor_auth.py) or its auth / model / tool-bridge behavior.
| name | detect-framework |
| description | Detect Python agent frameworks from code imports and map them to Omnigent executor types. Load when the user has existing agent code to integrate. |
When the user has existing Python code they want to integrate into Omnigent, detect the framework from import statements and recommend the appropriate executor type.
Ask the user for the path to their agent code (or look for Python files in the current directory if filesystem access is enabled).
Scan Python files for import patterns. Check in this priority order:
| Import pattern | Framework | Executor type |
|---|---|---|
import anthropic or from anthropic + agent patterns (e.g. Agent, tool, system prompt setup) | Claude SDK | claude_sdk |
import openai or from openai + agents patterns (e.g. Agent, Runner, function_tool) | OpenAI Agents SDK | agents_sdk |
from langgraph or import langgraph | LangGraph | Not natively supported yet |
from deepagents or import deepagents | DeepAgents | Not natively supported yet |
from langchain or import langchain | LangChain | Not natively supported yet |
from crewai or import crewai | CrewAI | Not natively supported yet |
from autogen or import autogen | AutoGen | Not natively supported yet |
| None of the above | Unknown | Not natively supported yet |
llm (default — no existing code)Generate a standard agent directory:
executor:
type: llm # or omit entirely (llm is the default)
claude_sdkThe user's Claude SDK code runs directly. Generate config that points to their entry module:
executor:
type: claude_sdk
agents_sdkThe user's OpenAI Agents SDK code runs directly:
executor:
type: agents_sdk
If the user's framework is not natively supported, let them know:
llm agent.https://github.com/dbczumar/omnigent/issues/new?title=...&body=...