--- title: "hello-agents vs clyro" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/datawhalechina-hello-agents-vs-getclyro-clyro" tools: ["datawhalechina-hello-agents", "getclyro-clyro"] --- # hello-agents vs clyro *GraphCanon updated Jul 15, 2026* ## Verdict Pick hello-agents when license: hello-agents is Other, clyro is Apache-2.0; pick clyro when license: clyro is Apache-2.0, hello-agents is Other. [hello-agents](https://hello-agents.datawhale.cc) reports 65k GitHub stars, 8.1k forks, and 144 open issues, last pushed Jul 10, 2026. [clyro](https://clyro.dev/) has 52 stars, 2 forks, and 0 open issues, last pushed Jul 2, 2026. Figures are from public GitHub metadata via [hello-agents's repository](https://github.com/datawhalechina/hello-agents) and [clyro's repository](https://github.com/getclyro/clyro). | | [hello-agents](/tools/datawhalechina-hello-agents.md) | [clyro](/tools/getclyro-clyro.md) | | --- | --- | --- | | Tagline | Course on building intelligent agents from scratch | Clyro is a governance platform for AI agents. While most tools let you watch agents fail, Clyro stops failures before they happen, catching infinite loops, runaway costs, and policy violations in real | | Stars | 65,432 | 52 | | Forks | 8,109 | 2 | | Open issues | 144 | 0 | | Language | Python | Python | | Adopt for | hello-agents is a comprehensive guide and hands-on tutorial for developing AI agents using LLMs (Large Language Models) and RAG methods. | - | | Persona | - | - | | Runtime | - | - | | License | hello-agents is covered under an unconventional license which may require further review before usage. | Apache-2.0 | | Categories | AI Agents, LLM Frameworks | AI Agents, Computer Vision, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [hello-agents](/tools/datawhalechina-hello-agents.md) | [clyro](/tools/getclyro-clyro.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 0d | 13d | | Open issues (now) | 144 | 0 | | Full report | [trust report](/tools/datawhalechina-hello-agents/trust.md) | [trust report](/tools/getclyro-clyro/trust.md) | ## Decision facts: hello-agents - **Requirements:** Min 4 GB RAM; Python knowledge assumed - **Adopt for:** hello-agents is a comprehensive guide and hands-on tutorial for developing AI agents using LLMs (Large Language Models) and RAG methods. - **License detail:** hello-agents is covered under an unconventional license which may require further review before usage. ## Choose when ### Choose hello-agents if… - License: hello-agents is Other, clyro is Apache-2.0. - Requirements: Min 4 GB RAM; Python knowledge assumed. - Tags unique to hello-agents: agent, llm, rag, tutorial. - You should use hello-agents if you are interested in practical, step-by-step instructions on building intelligent agents from the ground up. ### Choose clyro if… - License: clyro is Apache-2.0, hello-agents is Other. - Tags unique to clyro: agents, ai, ai-governance, anthropic. - Also covers Computer Vision. ## When NOT to use hello-agents - Avoid using hello-agents if you are looking for a quick, superficial introduction to AI agents; this tool focuses heavily on in-depth learning and practical application. - Do not opt for hello-agents if you want a more general AI development resource; unlike some competitors, it has a narrower focus specifically on agent creation with advanced methods like LLMs and RAG. ## When NOT to use clyro - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between hello-agents and clyro? hello-agents: Course on building intelligent agents from scratch. clyro: Clyro is a governance platform for AI agents. While most tools let you watch agents fail, Clyro stops failures before they happen, catching infinite loops, runaway costs, and policy violations in real. See the comparison table for live GitHub stats and shared categories. ### When should I choose hello-agents over clyro? Choose hello-agents over clyro when License: hello-agents is Other, clyro is Apache-2.0; Requirements: Min 4 GB RAM; Python knowledge assumed; Tags unique to hello-agents: agent, llm, rag, tutorial; You should use hello-agents if you are interested in practical, step-by-step instructions on building intelligent agents from the ground up. ### When should I choose clyro over hello-agents? Choose clyro over hello-agents when License: clyro is Apache-2.0, hello-agents is Other; Tags unique to clyro: agents, ai, ai-governance, anthropic; Also covers Computer Vision. ### When should I avoid hello-agents? Avoid using hello-agents if you are looking for a quick, superficial introduction to AI agents; this tool focuses heavily on in-depth learning and practical application. Do not opt for hello-agents if you want a more general AI development resource; unlike some competitors, it has a narrower focus specifically on agent creation with advanced methods like LLMs and RAG. ### When should I avoid clyro? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is hello-agents or clyro more popular on GitHub? hello-agents has more GitHub stars (65,432 vs 52). Stars measure visibility, not whether either tool fits your constraints. ### Are hello-agents and clyro open source? Yes - both are open-source projects on GitHub (hello-agents: Other, clyro: Apache-2.0). ### Where can I find alternatives to hello-agents or clyro? GraphCanon lists graph-backed alternatives at [hello-agents alternatives](/tools/datawhalechina-hello-agents/alternatives) and [clyro alternatives](/tools/getclyro-clyro/alternatives) ([hello-agents markdown twin](/tools/datawhalechina-hello-agents/alternatives.md), [clyro markdown twin](/tools/getclyro-clyro/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/datawhalechina-hello-agents-vs-getclyro-clyro.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, hello-agents or clyro? hello-agents: Very active. clyro: Active. 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 hello-agents and clyro? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [hello-agents trust report](/tools/datawhalechina-hello-agents/trust); [clyro trust report](/tools/getclyro-clyro/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=datawhalechina-hello-agents`](/api/graphcanon/graph?tool=datawhalechina-hello-agents) - 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/_