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 automatio
Install
The skill file stays in the publisher's repository.
Paste the copied command in a terminal. It installs this SKILL.md into that agent.
npx skills add Orchestra-Research/AI-Research-SKILLs --skill autogpt -a cursor -y
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.
Questions
How do I install autogpt-agents?
Download 14-agents/autogpt/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.
Where does autogpt-agents live?
The publisher keeps it at https://github.com/Orchestra-Research/AI-Research-SKILLs.
Which agents can use autogpt-agents?
Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.
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.
name: autogpt-agents
description: 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.
version: 1.0.0
author: Orchestra Research
license: MIT
tags: [Agents, AutoGPT, Autonomous Agents, Workflow Automation, Visual Builder, AI Platform]
dependencies: [autogpt-platform>=0.4.0]
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)
from forge import Ability, ability
@ability(
name="custom_search",
description="Search for information",
parameters={
"query": {"type": "string", "description": "Search query"}
}
)
def custom_search(query: str) -> str:
"""Custom search ability."""
# Implement search logic
result = perform_search(query)
return result
Benchmarking agents
Run benchmarks
# Run all benchmarks
./run benchmark
# Run specific category
./run benchmark --category coding
# Run with specific agent
./run benchmark --agent my-agent
Benchmark categories
Coding: Code generation and debugging
Retrieval: Information finding
Web: Web browsing and interaction
Writing: Text generation tasks
VCR cassettes
Benchmarks use recorded HTTP responses for reproducibility:
# Record new cassettes
./run benchmark --record
# Run with existing cassettes
./run benchmark --playback
Integrations
Adding credentials
Navigate to Profile > Integrations
Select provider (OpenAI, GitHub, Google, etc.)
Enter API keys or authorize OAuth
Credentials are encrypted and stored securely
Using credentials in blocks
Blocks automatically access user credentials:
class MyLLMBlock(Block):
def execute(self, inputs):
# Credentials are injected by the system
credentials = self.get_credentials("openai")
client = OpenAI(api_key=credentials.api_key)
# ...