--- title: "AutoGPT vs commands" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/significant-gravitas-autogpt-vs-wshobson-commands" tools: ["significant-gravitas-autogpt", "wshobson-commands"] --- # AutoGPT vs commands *GraphCanon updated Jul 15, 2026* ## Verdict Pick AutoGPT when license: AutoGPT is Other, commands is MIT; pick commands when license: commands is MIT, AutoGPT is Other. [AutoGPT](https://agpt.co) reports 185k GitHub stars, 46k forks, and 494 open issues, last pushed Jul 11, 2026. [commands](https://sethhobson.com) has 2.6k stars, 291 forks, and 3 open issues, last pushed Oct 12, 2025. Figures are from public GitHub metadata via [AutoGPT's repository](https://github.com/Significant-Gravitas/AutoGPT) and [commands's repository](https://github.com/wshobson/commands). | | [AutoGPT](/tools/significant-gravitas-autogpt.md) | [commands](/tools/wshobson-commands.md) | | --- | --- | --- | | Tagline | AutoGPT is the vision of accessible AI for everyone, to use and to build on. | A collection of production-ready slash commands for Claude Code | | Stars | 185,464 | 2,564 | | Forks | 46,111 | 291 | | Open issues | 494 | 3 | | Language | Python | - | | Adopt for | AutoGPT is a Python-based tool for creating accessible autonomous AI agents that can leverage various LLM APIs including OpenAI's GPT and Anthropic's Claude. | - | | Persona | - | - | | Runtime | - | - | | License | Other | MIT | | Categories | AI Agents, LLM Frameworks | AI Agents, Inference & Serving, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [AutoGPT](/tools/significant-gravitas-autogpt.md) | [commands](/tools/wshobson-commands.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 276d | | Open issues (now) | 494 | 3 | | Owner type | Organization | User | | Full report | [trust report](/tools/significant-gravitas-autogpt/trust.md) | [trust report](/tools/wshobson-commands/trust.md) | ## Decision facts: AutoGPT - **Adopt for:** AutoGPT is a Python-based tool for creating accessible autonomous AI agents that can leverage various LLM APIs including OpenAI's GPT and Anthropic's Claude. ## Choose when ### Choose AutoGPT if… - License: AutoGPT is Other, commands is MIT. - Tags unique to AutoGPT: agentic-ai, agents, artificial-intelligence, autonomous-agents. - Also covers LLM Frameworks. - When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise. ### Choose commands if… - License: commands is MIT, AutoGPT is Other. - Tags unique to commands: ai-agents, anthropic, automation, claude code. - Also covers Inference & Serving, Vector Databases. ## When NOT to use AutoGPT - Avoid if you require absolute control over the underlying AI infrastructure and APIs used by your autonomous agents, as AutoGPT imposes its own framework. - If your project demands proprietary or specialized models that aren't supported by AutoGPT's API ecosystem (e.g., custom TensorFlow or PyTorch models), consider other tools. ## When NOT to use commands - Last GitHub push was 276 days ago (slowing maintenance, Oct 12, 2025). Validate activity before betting a new project on commands. - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## Common questions ### What is the difference between AutoGPT and commands? AutoGPT: AutoGPT is the vision of accessible AI for everyone, to use and to build on.. commands: A collection of production-ready slash commands for Claude Code. See the comparison table for live GitHub stats and shared categories. ### When should I choose AutoGPT over commands? Choose AutoGPT over commands when License: AutoGPT is Other, commands is MIT; Tags unique to AutoGPT: agentic-ai, agents, artificial-intelligence, autonomous-agents; Also covers LLM Frameworks; When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise. ### When should I choose commands over AutoGPT? Choose commands over AutoGPT when License: commands is MIT, AutoGPT is Other; Tags unique to commands: ai-agents, anthropic, automation, claude code; Also covers Inference & Serving, Vector Databases. ### When should I avoid AutoGPT? Avoid if you require absolute control over the underlying AI infrastructure and APIs used by your autonomous agents, as AutoGPT imposes its own framework. If your project demands proprietary or specialized models that aren't supported by AutoGPT's API ecosystem (e.g., custom TensorFlow or PyTorch models), consider other tools. ### When should I avoid commands? Last GitHub push was 276 days ago (slowing maintenance, Oct 12, 2025). Validate activity before betting a new project on commands. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is AutoGPT or commands more popular on GitHub? AutoGPT has more GitHub stars (185,464 vs 2,564). Stars measure visibility, not whether either tool fits your constraints. ### Are AutoGPT and commands open source? Yes - both are open-source projects on GitHub (AutoGPT: Other, commands: MIT). ### Where can I find alternatives to AutoGPT or commands? GraphCanon lists graph-backed alternatives at [AutoGPT alternatives](/tools/significant-gravitas-autogpt/alternatives) and [commands alternatives](/tools/wshobson-commands/alternatives) ([AutoGPT markdown twin](/tools/significant-gravitas-autogpt/alternatives.md), [commands markdown twin](/tools/wshobson-commands/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/significant-gravitas-autogpt-vs-wshobson-commands.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, AutoGPT or commands? AutoGPT: Very active. commands: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for AutoGPT and commands? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [AutoGPT trust report](/tools/significant-gravitas-autogpt/trust); [commands trust report](/tools/wshobson-commands/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=significant-gravitas-autogpt`](/api/graphcanon/graph?tool=significant-gravitas-autogpt) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_