--- title: "Prompt-Engineering-Guide vs hello-agents" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dair-ai-prompt-engineering-guide-vs-datawhalechina-hello-agents" tools: ["dair-ai-prompt-engineering-guide", "datawhalechina-hello-agents"] --- # Prompt-Engineering-Guide vs hello-agents *GraphCanon updated Aug 18, 2026* ## Verdict Pick Prompt-Engineering-Guide if decision-critical facts for Prompt-Engineering-Guide; pick hello-agents if hello-agents is a comprehensive guide and hands-on tutorial for developing AI agents using LLMs (Large Language Models) and RAG methods. [Prompt-Engineering-Guide](https://www.promptingguide.ai/) reports 78k GitHub stars, 8.5k forks, and 279 open issues, last pushed Mar 11, 2026. [hello-agents](https://hello-agents.datawhale.cc) has 73k stars, 9.1k forks, and 155 open issues, last pushed Aug 14, 2026. Figures are from public GitHub metadata via [Prompt-Engineering-Guide's repository](https://github.com/dair-ai/Prompt-Engineering-Guide) and [hello-agents's repository](https://github.com/datawhalechina/hello-agents). | | [Prompt-Engineering-Guide](/tools/dair-ai-prompt-engineering-guide.md) | [hello-agents](/tools/datawhalechina-hello-agents.md) | | --- | --- | --- | | Tagline | Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents | Course on building intelligent agents from scratch | | Stars | 77,531 | 73,126 | | Forks | 8,518 | 9,108 | | Open issues | 279 | 155 | | Language | MDX | Python | | Adopt for | Decision-critical facts for Prompt-Engineering-Guide | 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 | MIT | hello-agents is covered under an unconventional license which may require further review before usage. | | Categories | AI Agents, LLM Frameworks | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Prompt-Engineering-Guide](/tools/dair-ai-prompt-engineering-guide.md) | [hello-agents](/tools/datawhalechina-hello-agents.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Very active (96%) | | Days since push | 159d | 1d | | Open issues (now) | 279 | 155 | | Stars delta | +829 (30d) | +6.4k (30d) | | Open issues delta | +3 (30d) | +8 (30d) | | Full report | [trust report](/tools/dair-ai-prompt-engineering-guide/trust.md) | [trust report](/tools/datawhalechina-hello-agents/trust.md) | **Typed relationship:** Prompt-Engineering-Guide _(integrates with)_ hello-agents Hello-Agents can utilize prompt engineering guides from the dair.ai project to enhance the development of intelligent agents, improving the creation and refinement of prompts for LLMs. ## Decision facts: Prompt-Engineering-Guide - **Adopt for:** Decision-critical facts for Prompt-Engineering-Guide ## 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 Prompt-Engineering-Guide if… - Prompt-Engineering-Guide is primarily MDX; hello-agents is Python. - License: Prompt-Engineering-Guide is MIT, hello-agents is Other. - Hello-Agents can utilize prompt engineering guides from the dair.ai project to enhance the development of intelligent agents, improving the creation and refinement of prompts for LLMs. - Tags unique to Prompt-Engineering-Guide: agents, ai-agents, chatgpt, deep-learning. - When you seek comprehensive documentation and educational materials specifically focused on the nuance of prompt engineering techniques. ### Choose hello-agents if… - hello-agents is primarily Python; Prompt-Engineering-Guide is MDX. - License: hello-agents is Other, Prompt-Engineering-Guide is MIT. - Requirements: Min 4 GB RAM; Python knowledge assumed. - Hello-Agents can utilize prompt engineering guides from the dair.ai project to enhance the development of intelligent agents, improving the creation and refinement of prompts for LLMs. - Tags unique to hello-agents: 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 NOT to use Prompt-Engineering-Guide - Avoid using if your focus is entirely on deep-learning frameworks without a need for detailed instructions or examples related to prompt crafting. - Not suitable when you require tools that go beyond guiding materials, such as custom prompts or direct software plugins provided by competitors focused more on practical implementation over learning. ## 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. ## Common questions ### What is the difference between Prompt-Engineering-Guide and hello-agents? Prompt-Engineering-Guide: Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents. hello-agents: Course on building intelligent agents from scratch. See the comparison table for live GitHub stats and shared categories. ### When should I choose Prompt-Engineering-Guide over hello-agents? Choose Prompt-Engineering-Guide over hello-agents when Prompt-Engineering-Guide is primarily MDX; hello-agents is Python; License: Prompt-Engineering-Guide is MIT, hello-agents is Other; Hello-Agents can utilize prompt engineering guides from the dair.ai project to enhance the development of intelligent agents, improving the creation and refinement of prompts for LLMs; Tags unique to Prompt-Engineering-Guide: agents, ai-agents, chatgpt, deep-learning; When you seek comprehensive documentation and educational materials specifically focused on the nuance of prompt engineering techniques. ### When should I choose hello-agents over Prompt-Engineering-Guide? Choose hello-agents over Prompt-Engineering-Guide when hello-agents is primarily Python; Prompt-Engineering-Guide is MDX; License: hello-agents is Other, Prompt-Engineering-Guide is MIT; Requirements: Min 4 GB RAM; Python knowledge assumed; Hello-Agents can utilize prompt engineering guides from the dair.ai project to enhance the development of intelligent agents, improving the creation and refinement of prompts for LLMs; Tags unique to hello-agents: 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 avoid Prompt-Engineering-Guide? Avoid using if your focus is entirely on deep-learning frameworks without a need for detailed instructions or examples related to prompt crafting. Not suitable when you require tools that go beyond guiding materials, such as custom prompts or direct software plugins provided by competitors focused more on practical implementation over learning. ### 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. ### Is Prompt-Engineering-Guide or hello-agents more popular on GitHub? Prompt-Engineering-Guide has more GitHub stars (77,531 vs 73,126). Stars measure visibility, not whether either tool fits your constraints. ### Are Prompt-Engineering-Guide and hello-agents open source? Yes - both are open-source projects on GitHub (Prompt-Engineering-Guide: MIT, hello-agents: Other). ### Where can I find alternatives to Prompt-Engineering-Guide or hello-agents? GraphCanon lists graph-backed alternatives at [Prompt-Engineering-Guide alternatives](/tools/dair-ai-prompt-engineering-guide/alternatives) and [hello-agents alternatives](/tools/datawhalechina-hello-agents/alternatives) ([Prompt-Engineering-Guide markdown twin](/tools/dair-ai-prompt-engineering-guide/alternatives.md), [hello-agents markdown twin](/tools/datawhalechina-hello-agents/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/dair-ai-prompt-engineering-guide-vs-datawhalechina-hello-agents.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Prompt-Engineering-Guide or hello-agents? Prompt-Engineering-Guide: Slowing. hello-agents: Very 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 Prompt-Engineering-Guide and hello-agents? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Prompt-Engineering-Guide trust report](/tools/dair-ai-prompt-engineering-guide/trust); [hello-agents trust report](/tools/datawhalechina-hello-agents/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=dair-ai-prompt-engineering-guide`](/api/graphcanon/graph?tool=dair-ai-prompt-engineering-guide) - 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/_