How do I install the Detect Framework skill?

Run npx skillmds@latest add gabrielmoreira/detect-framework in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Detect Framework safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Detect Framework?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Detect Framework free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Detect Framework?

gabrielmoreira (@gabrielmoreira) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Detect Framework by gabrielmoreira — Agent Skill

Name: Detect Framework
Rating: 4.2 (5 reviews)
Author: gabrielmoreira

File contents

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

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

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:

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:

executor:
  type: claude_sdk

`agents_sdk`

The user's OpenAI Agents SDK code runs directly:

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=...

---name: detect-frameworkdescription: Detect Python agent frameworks from code imports and map them to Omnigent executor types. Load when the user has existing agent code to integrate.--- # 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=...`

Frequently asked questions

Detect Framework