Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add liortesta/ClawdAgent --skill autogptgit clone --depth 1 https://github.com/liortesta/ClawdAgentWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/liortesta/clawdagent/autogpt)<a href="https://agentmods.dev/skills/liortesta/clawdagent/autogpt"><img src="https://agentmods.dev/badge/skills/liortesta/clawdagent/autogpt.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00039 | $0.02233 |
| Opus 5 | $0.00019 | $0.01117 |
| Sonnet 5 | $0.00008 | $0.00447 |
| Haiku 4.5 | $0.00004 | $0.00223 |
Grade A, and why
autogpt-agents scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to autogpt-agents — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 404 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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)
# 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
cp .env.example .env
npm install
npm run dev
Access the platform
- Frontend UI: http://localhost:3000
- Backend API: http://localhost:8006/api
- WebSocket: ws://localhost:8001/ws
Architecture overview
AutoGPT has two main systems:
AutoGPT Platform (Production)
- Visual agent builder with React frontend
- FastAPI backend with execution engine
- PostgreSQL + Redis + RabbitMQ infrastructure
AutoGPT Classic (Development)
- Forge: Agent development toolkit
- Benchmark: Performance testing framework
- CLI: Command-line interface for development
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 404 lines · 39 tokens per session scan A 4b16c070da99
autogpt-agents is a skill published in the GitHub repository liortesta/ClawdAgent (11 stars, last pushed 11d ago), licensed Apache-2.0. It adds 39 tokens to every session and 2,233 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to autogpt-agents, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
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.
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.
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.
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.
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.
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.