--- title: "chatgpt_system_prompt vs agents-from-scratch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/louisshark-chatgpt-system-prompt-vs-pguso-agents-from-scratch" tools: ["louisshark-chatgpt-system-prompt", "pguso-agents-from-scratch"] --- # chatgpt_system_prompt vs agents-from-scratch *GraphCanon updated Aug 12, 2026* ## Verdict Pick chatgpt_system_prompt if chatgpt_system_prompt is an essential resource for developers specifically using GPT models needing a collection of system prompts alongside education on the critical issue of prompt injection and leaking; pick agents-from-scratch if agents-from-scratch is for those who want absolute control over their AI agent development using only local resources and Python, focusing on deep learning without relying on. [chatgpt_system_prompt](https://github.com/LouisShark/chatgpt_system_prompt) reports 11k GitHub stars, 1.5k forks, and 1 open issues, last pushed Jul 27, 2026. [agents-from-scratch](https://github.com/pguso/agents-from-scratch) has 954 stars, 240 forks, and 3 open issues, last pushed Jul 25, 2026. Figures are from public GitHub metadata via [chatgpt_system_prompt's repository](https://github.com/LouisShark/chatgpt_system_prompt) and [agents-from-scratch's repository](https://github.com/pguso/agents-from-scratch). | | [chatgpt_system_prompt](/tools/louisshark-chatgpt-system-prompt.md) | [agents-from-scratch](/tools/pguso-agents-from-scratch.md) | | --- | --- | --- | | Tagline | A collection of GPT system prompts and knowledge on prompt injection leaking | Build AI agents locally without relying on frameworks or cloud APIs. | | Stars | 10,699 | 954 | | Forks | 1,468 | 240 | | Open issues | 1 | 3 | | Language | HTML | Python | | Adopt for | chatgpt_system_prompt is an essential resource for developers specifically using GPT models needing a collection of system prompts alongside education on the critical issue of prompt injection and leaking. | agents-from-scratch is for those who want absolute control over their AI agent development using only local resources and Python, focusing on deep learning without relying on external frameworks or cloud dependencies. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT License: Permissive licensing allowing free use and distribution for both commercial and non-commercial purposes. | | Categories | Developer Tools | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [chatgpt_system_prompt](/tools/louisshark-chatgpt-system-prompt.md) | [agents-from-scratch](/tools/pguso-agents-from-scratch.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 0d | 18d | | Open issues (now) | 1 | 3 | | Full report | [trust report](/tools/louisshark-chatgpt-system-prompt/trust.md) | [trust report](/tools/pguso-agents-from-scratch/trust.md) | ## Decision facts: chatgpt_system_prompt - **Adopt for:** chatgpt_system_prompt is an essential resource for developers specifically using GPT models needing a collection of system prompts alongside education on the critical issue of prompt injection and leaking. ## Decision facts: agents-from-scratch - **Requirements:** Min 8 GB RAM; Local large language model availability is critical as the tool does not utilize any cloud APIs. - **Adopt for:** agents-from-scratch is for those who want absolute control over their AI agent development using only local resources and Python, focusing on deep learning without relying on external frameworks or cloud dependencies. - **License detail:** MIT License: Permissive licensing allowing free use and distribution for both commercial and non-commercial purposes. ## Choose when ### Choose chatgpt_system_prompt if… - chatgpt_system_prompt is primarily HTML; agents-from-scratch is Python. - Tags unique to chatgpt_system_prompt: gpt. - When working with GPT models, you seek direct examples and guidance related to secure prompt design ### Choose agents-from-scratch if… - agents-from-scratch is primarily Python; chatgpt_system_prompt is HTML. - Requirements: Min 8 GB RAM; Local large language model availability is critical as the tool does not utilize any cloud APIs.. - Tags unique to agents-from-scratch: agent-architecture, ai-agents, llm, local-llm. - Also covers AI Agents. - You plan to teach yourself or others about the fundamentals of creating AI agents from ground zero with complete transparency into each layer of architecture. ## When NOT to use chatgpt_system_prompt - For developing or troubleshooting other types of AI models not based on GPT architecture which might have different requirements for system prompts - In scenarios where the focus is on learning generic machine learning principles rather than specific to GPT's prompt engineering considerations and limitations ## When NOT to use agents-from-scratch - You are working on an application that needs to be deployed quickly. The tool's approach from first principles can be time-consuming compared to using established frameworks. - If you need scalability or cloud capabilities such as easy scaling with demand, this tool will not provide these features since it strictly operates on local infrastructure. ## Common questions ### What is the difference between chatgpt_system_prompt and agents-from-scratch? chatgpt_system_prompt: A collection of GPT system prompts and knowledge on prompt injection leaking. agents-from-scratch: Build AI agents locally without relying on frameworks or cloud APIs.. See the comparison table for live GitHub stats and shared categories. ### When should I choose chatgpt_system_prompt over agents-from-scratch? Choose chatgpt_system_prompt over agents-from-scratch when chatgpt_system_prompt is primarily HTML; agents-from-scratch is Python; Tags unique to chatgpt_system_prompt: gpt; When working with GPT models, you seek direct examples and guidance related to secure prompt design. ### When should I choose agents-from-scratch over chatgpt_system_prompt? Choose agents-from-scratch over chatgpt_system_prompt when agents-from-scratch is primarily Python; chatgpt_system_prompt is HTML; Requirements: Min 8 GB RAM; Local large language model availability is critical as the tool does not utilize any cloud APIs.; Tags unique to agents-from-scratch: agent-architecture, ai-agents, llm, local-llm; Also covers AI Agents; You plan to teach yourself or others about the fundamentals of creating AI agents from ground zero with complete transparency into each layer of architecture. ### When should I avoid chatgpt_system_prompt? For developing or troubleshooting other types of AI models not based on GPT architecture which might have different requirements for system prompts In scenarios where the focus is on learning generic machine learning principles rather than specific to GPT's prompt engineering considerations and limitations ### When should I avoid agents-from-scratch? You are working on an application that needs to be deployed quickly. The tool's approach from first principles can be time-consuming compared to using established frameworks. If you need scalability or cloud capabilities such as easy scaling with demand, this tool will not provide these features since it strictly operates on local infrastructure. ### Is chatgpt_system_prompt or agents-from-scratch more popular on GitHub? chatgpt_system_prompt has more GitHub stars (10,699 vs 954). Stars measure visibility, not whether either tool fits your constraints. ### Are chatgpt_system_prompt and agents-from-scratch open source? Yes - both are open-source projects on GitHub (chatgpt_system_prompt: MIT, agents-from-scratch: MIT). ### Where can I find alternatives to chatgpt_system_prompt or agents-from-scratch? GraphCanon lists graph-backed alternatives at [chatgpt_system_prompt alternatives](/tools/louisshark-chatgpt-system-prompt/alternatives) and [agents-from-scratch alternatives](/tools/pguso-agents-from-scratch/alternatives) ([chatgpt_system_prompt markdown twin](/tools/louisshark-chatgpt-system-prompt/alternatives.md), [agents-from-scratch markdown twin](/tools/pguso-agents-from-scratch/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/louisshark-chatgpt-system-prompt-vs-pguso-agents-from-scratch.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, chatgpt_system_prompt or agents-from-scratch? chatgpt_system_prompt: Very active. agents-from-scratch: 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 chatgpt_system_prompt and agents-from-scratch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [chatgpt_system_prompt trust report](/tools/louisshark-chatgpt-system-prompt/trust); [agents-from-scratch trust report](/tools/pguso-agents-from-scratch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=louisshark-chatgpt-system-prompt`](/api/graphcanon/graph?tool=louisshark-chatgpt-system-prompt) - 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/_