"Route AutoGPT Platform self-hosting, backend, frontend, and legacy
Scanned 9/8/2026
Install to Claude Code
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---
name: autogpt
description: "Route AutoGPT Platform self-hosting, backend, frontend, and legacy
Classic agent work to focused operating guidance."
metadata:
disco-role: operating
disable-model-invocation: true
license: NOASSERTION
---
# AutoGPT
Use this skill for the AutoGPT monorepo. Start by deciding whether the task is
for the current **AutoGPT Platform** or the unsupported **Classic** suite.
Platform is the maintained self-hosted product; Classic is retained for
educational and historical use and has known dependency/security limitations.
## Quick routing
| If the task involves | Read next |
| --- | --- |
| Docker Compose, `.env` setup, local services, self-host upgrade, ports, or local LLM configuration | [platform-stack](sub-skills/platform-stack/SKILL.md) |
| FastAPI routes, graph execution, blocks, integrations, Prisma, model catalog, backend CLI, or Python tests | [platform-backend](sub-skills/platform-backend/SKILL.md) |
| Next.js pages, Builder/Copilot/Library/Marketplace UI, generated API hooks, Tailwind/design system, or frontend tests | [platform-frontend](sub-skills/platform-frontend/SKILL.md) |
| `autogpt`/`serve` CLI, Forge, workspace permissions, or `direct-benchmark` | [classic-agents](sub-skills/classic-agents/SKILL.md) |
For a backend endpoint plus a UI consumer, begin with `platform-backend`, then
use `platform-frontend` for the generated hook and screen work. For local
end-to-end validation, also read `platform-stack` before starting services.
## Operating sequence
1. Confirm the product surface and the smallest affected package.
2. Read the selected sub-skill and its linked references before changing code.
3. Preserve the repository's branch, secret, test, and formatting rules.
4. Choose the narrowest safe validation first; do not start Docker services,
browser tests, benchmarks, migrations, or credentialed workflows merely to
inspect them.
5. Escalate to cross-surface validation only when the task actually crosses a
backend/frontend, API/schema, or runtime boundary.
## Fast orientation
- AutoGPT Platform combines a Python backend, a Next.js frontend, shared Python
libraries, Docker services, visual agent graphs, blocks, integrations, and a
marketplace.
- The Platform's standard local stack uses Docker Compose; the backend and
frontend can also run separately for active development.
- Classic is one Poetry project containing `autogpt`, `forge`, and
`direct_benchmark`. Treat it as unsupported and avoid presenting it as the
recommended path for new production work.
Read [repository map](references/repository-map.md) for package boundaries and
common change locations. Read [contributor guidance](references/contributor-guidance.md)
when a task will modify code or documentation. Read
[cross-cutting troubleshooting](references/troubleshooting.md) for setup,
secrets, service, and version failures.
## Public setup anchors
Use the package-specific sub-skills for complete setup. Minimal public commands
are:
```bash
cd autogpt_platform && make init-env && make start-core
cd autogpt_platform/backend && poetry install
cd autogpt_platform/frontend && corepack enable && pnpm install
cd classic && poetry install
```
Run only the commands needed for the chosen surface. Do not combine Platform
backend and Classic dependencies into one Python environment unless a task
explicitly asks for that experiment.
## Safe reusable helper
Run `python scripts/autogpt_repo_probe.py --repo <checkout>` to identify the
major AutoGPT surfaces and missing host tools without starting services or
editing the checkout. Use `--json` when another tool needs structured output.
## Scope limits
This operating graph describes the checked source revision recorded in
[repo provenance](references/repo-provenance.md). It does not provide secrets,
managed-cloud access, external provider credentials, model downloads, or a
promise that Classic dependencies are safe or maintained.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
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