---
name: Framework Detection
slug: framework-detection
category: AI Engineering
description: Framework Detection scans Python imports in existing agent code and maps them to Omnigent executor types. Use it when integrating existing Python agent code into Omnigent.
github: "https://github.com/omnigent-ai/omnigent/tree/main/omnigent/onboarding/agent/skills/detect-framework"
language: Python
stars: 8855
forks: 1336
install: "npx degit https://github.com/omnigent-ai/omnigent/tree/main/omnigent/onboarding/agent/skills/detect-framework ~/.claude/skills/detect-framework"
installs_to: ~/.claude/skills/detect-framework
source_path: omnigent/onboarding/agent/skills/detect-framework/SKILL.md
collection_size: 24
category_size: 2451
collection_url: "https://dirskills.com/collections/omnigent-ai/omnigent"
added: 2026-08-15T06:50:46.005Z
last_synced: 2026-08-15T06:50:46.005Z
canonical_url: "https://dirskills.com/skills/framework-detection"
---

# Framework Detection

Framework Detection scans Python imports in existing agent code and maps them to Omnigent executor types. Use it when integrating existing Python agent code into Omnigent.

**Install:**

```bash
npx degit https://github.com/omnigent-ai/omnigent/tree/main/omnigent/onboarding/agent/skills/detect-framework ~/.claude/skills/detect-framework
```

## README

# Framework Detection

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.

## Detection Procedure

1. Ask the user for the path to their agent code (or look for Python
   files in the current directory if filesystem access is enabled).

2. 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 |

3. Report what you found and recommend the executor type.

## What to generate for each executor type

### `llm` (default — no existing code)

Generate a standard agent directory:
```yaml
executor:
  type: llm  # or omit entirely (llm is the default)
```

### `claude_sdk`

The user's Claude SDK code runs directly. Generate config that points
to their entry module:
```yaml
executor:
  type: claude_sdk
```

### `agents_sdk`

The user's OpenAI Agents SDK code runs directly:
```yaml
executor:
  type: agents_sdk
```

## Asking about unsupported frameworks

If the user's framework is not natively supported, let them know:
- Explain that Omnigent does not currently have a supported executor for that framework.
- Offer to show them a pre-filled GitHub issue URL requesting first-class
  support for their framework.
- If they want to start fresh instead, recommend generating a standard `llm` agent.
- The issue URL format: `https://github.com/dbczumar/omnigent/issues/new?title=...&body=...`