--- title: "agentscope vs skyagi" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentscope-ai-agentscope-vs-litanlitudan-skyagi" tools: ["agentscope-ai-agentscope", "litanlitudan-skyagi"] --- # agentscope vs skyagi *GraphCanon updated Aug 16, 2026* ## Verdict Pick agentscope if agentscope is a Python-based development tool focused on creating transparent and trustworthy AI agents. It supports the creation of both single and multi-agent systems incorporating large language models into its design; pick skyagi if skyAGI is a development tool focusing on simulating human behavior using large language models and is available under the Apache-2.0 license. [agentscope](https://docs.agentscope.io/) reports 29k GitHub stars, 3.4k forks, and 354 open issues, last pushed Aug 14, 2026. [skyagi](https://skyagi.ai) has 778 stars, 56 forks, and 42 open issues, last pushed Sep 21, 2023. Figures are from public GitHub metadata via [agentscope's repository](https://github.com/agentscope-ai/agentscope) and [skyagi's repository](https://github.com/litanlitudan/skyagi). | | [agentscope](/tools/agentscope-ai-agentscope.md) | [skyagi](/tools/litanlitudan-skyagi.md) | | --- | --- | --- | | Tagline | Build and run agents you can see, understand and trust. | SkyAGI provides emerging human-behavior simulation capability in LLM. | | Stars | 28,973 | 778 | | Forks | 3,367 | 56 | | Open issues | 354 | 42 | | Language | Python | TypeScript | | Adopt for | agentscope is a Python-based development tool focused on creating transparent and trustworthy AI agents. It supports the creation of both single and multi-agent systems incorporating large language models into its design | SkyAGI is a development tool focusing on simulating human behavior using large language models and is available under the Apache-2.0 license. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | AI Agents, LLM Frameworks | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentscope](/tools/agentscope-ai-agentscope.md) | [skyagi](/tools/litanlitudan-skyagi.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 2d | 1058d | | Open issues (now) | 354 | 42 | | Stars delta | +1.0k (30d) | +1 (30d) | | Open issues delta | +70 (30d) | +1 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/agentscope-ai-agentscope/trust.md) | [trust report](/tools/litanlitudan-skyagi/trust.md) | ## Shared compatibility - **Python**: [agentscope](/tools/agentscope-ai-agentscope.md) - Python runtime; [skyagi](/tools/litanlitudan-skyagi.md) - Python runtime ## Decision facts: agentscope - **Adopt for:** agentscope is a Python-based development tool focused on creating transparent and trustworthy AI agents. It supports the creation of both single and multi-agent systems incorporating large language models into its design ## Decision facts: skyagi - **Requirements:** It requires a valid OpenAI API key for operational purposes. - **Adopt for:** SkyAGI is a development tool focusing on simulating human behavior using large language models and is available under the Apache-2.0 license. ## Choose when ### Choose agentscope if… - agentscope is primarily Python; skyagi is TypeScript. - Tags unique to agentscope: agent, chatbot, large language models, llm-agent. - - You need to develop AI agents where transparency and interpretability are critical. ### Choose skyagi if… - skyagi is primarily TypeScript; agentscope is Python. - Requirements: It requires a valid OpenAI API key for operational purposes.. - Tags unique to skyagi: ai-agent, aigc, langchain, language-model. - if you aim to integrate highly dynamic, human-like behavioral characteristics in AI agents within your application ## When NOT to use agentscope - - If your project does not benefit from the transparency features offered by agentscope, and less emphasis is placed on interpretability and more on specialized machine learning tasks without a need ## When NOT to use skyagi - if your project does not need the complexity of simulating detailed human behavior through LLMs and prefers more straightforward automations - when you have constraints that do not allow for third-party API usage, as SkyAGI depends on an external OPENAI_API_KEY to function ## Common questions ### What is the difference between agentscope and skyagi? agentscope: Build and run agents you can see, understand and trust.. skyagi: SkyAGI provides emerging human-behavior simulation capability in LLM.. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentscope over skyagi? Choose agentscope over skyagi when agentscope is primarily Python; skyagi is TypeScript; Tags unique to agentscope: agent, chatbot, large language models, llm-agent; - You need to develop AI agents where transparency and interpretability are critical. ### When should I choose skyagi over agentscope? Choose skyagi over agentscope when skyagi is primarily TypeScript; agentscope is Python; Requirements: It requires a valid OpenAI API key for operational purposes.; Tags unique to skyagi: ai-agent, aigc, langchain, language-model; if you aim to integrate highly dynamic, human-like behavioral characteristics in AI agents within your application. ### When should I avoid agentscope? - If your project does not benefit from the transparency features offered by agentscope, and less emphasis is placed on interpretability and more on specialized machine learning tasks without a need ### When should I avoid skyagi? if your project does not need the complexity of simulating detailed human behavior through LLMs and prefers more straightforward automations when you have constraints that do not allow for third-party API usage, as SkyAGI depends on an external OPENAI_API_KEY to function ### Is agentscope or skyagi more popular on GitHub? agentscope has more GitHub stars (28,973 vs 778). Stars measure visibility, not whether either tool fits your constraints. ### Are agentscope and skyagi open source? Yes - both are open-source projects on GitHub (agentscope: Apache-2.0, skyagi: Apache-2.0). ### Where can I find alternatives to agentscope or skyagi? GraphCanon lists graph-backed alternatives at [agentscope alternatives](/tools/agentscope-ai-agentscope/alternatives) and [skyagi alternatives](/tools/litanlitudan-skyagi/alternatives) ([agentscope markdown twin](/tools/agentscope-ai-agentscope/alternatives.md), [skyagi markdown twin](/tools/litanlitudan-skyagi/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/agentscope-ai-agentscope-vs-litanlitudan-skyagi.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentscope or skyagi? agentscope: Very active. skyagi: Dormant. 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 agentscope and skyagi? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentscope trust report](/tools/agentscope-ai-agentscope/trust); [skyagi trust report](/tools/litanlitudan-skyagi/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agentscope-ai-agentscope`](/api/graphcanon/graph?tool=agentscope-ai-agentscope) - 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/_