Agent skill · Workflow & Productivity

autogpt-agents

Autonomous AI agent platform for building and deploying continuous agents. Use when creating visual workflow agents, deploying persistent autonomous agents, or building complex multi-step AI automation systems.

Orchestra-Researchgithub.com/Orchestra-ResearchGitHub ↗
claude-codecodexMIT
Install
npx skills add Orchestra-Research/AI-Research-SKILLs --skill autogpt --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 3
SKILL.md size: 9 KB
Bundled scripts: none
Version: 1.0.0
Declared author: Orchestra Research
Requires: [autogpt-platform>=0.4.0]
Path: 14-agents/autogpt/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 11,391
Language: TeX
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# AutoGPT - Autonomous AI Agent Platform Comprehensive platform for building, deploying, and managing continuous AI agents through a visual interface or development toolkit. ## When to use AutoGPT **Use AutoGPT when:** - Building autonomous agents that run continuously - Creating visual workflow-based AI agents - Deploying agents with external triggers (webhooks, schedules) - Building complex multi-step automation pipelines - Need a no-code/low-code agent builder **Key features:** - **Visual Agent Builder**: Drag-and-drop node-based workflow editor - **Continuous Execution**: Agents run persistently with triggers - **Marketplace**: Pre-built agents and blocks to share/reuse - **Block System**: Modular components for LLM, tools, integrations - **Forge Toolkit**: Developer tools for custom agent creation - **Benchmark System**: Standardized agent performance testing **Use alternatives instead:** - **LangChain/LlamaIndex**: If you need more control over agent logic - **CrewAI**: For role-based multi-agent collaboration - **OpenAI Assistants**: For simple hosted agent deployments - **Semantic Kernel**: For Microsoft ecosystem integration ## Quick start ### Installation (Docker) ```bash

What's inside
Steps it walks through
  1. When to use AutoGPT
  2. Quick start
  3. Installation (Docker)
  4. Access the platform
  5. Architecture overview
  6. AutoGPT Platform (Production)
  7. AutoGPT Classic (Development)
  8. Core concepts
  9. Graphs and nodes
  10. Blocks
  11. Execution flow
  12. Building agents
  13. Using the visual builder
  14. Available blocks
Ships with 2 files
  • references/advanced-usage.md
  • references/troubleshooting.md
Commands it runs
Clone repository
git clone https://github.com/Significant-Gravitas/AutoGPT.git
cd AutoGPT/autogpt_platform
Copy environment file
cp .env.example .env
Start backend services
docker compose up -d --build
Start frontend (in separate terminal)
cd frontend
npm install
More from AI-Research-SKILLs
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About this skill
What does the autogpt-agents skill do?

Autonomous AI agent platform for building and deploying continuous agents. Use when creating visual workflow agents, deploying persistent autonomous agents, or building complex multi-step AI automation systems.

How do I install it?

Run `npx skills add Orchestra-Research/AI-Research-SKILLs --skill autogpt --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From Orchestra-Research/AI-Research-SKILLs, a repository with 11,391 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going