--- title: "promptext vs Awesome-Prompt-Engineering" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/1broseidon-promptext-vs-promptslab-awesome-prompt-engineering" tools: ["1broseidon-promptext", "promptslab-awesome-prompt-engineering"] --- # promptext vs Awesome-Prompt-Engineering *GraphCanon updated Aug 2, 2026* ## Verdict Pick promptext if for developers seeking a tool to streamline AI interaction with codebases via context extraction, promptext stands out for its Go-centric design and CLI focus; pick Awesome-Prompt-Engineering if awesome-Prompt-Engineering curates resources tailored for GPT, ChatGPT, PaLM prompt engineering in TypeScript under Apache-2.0 license. [promptext](https://chain.sh/promptext) reports 22 GitHub stars, 1 forks, and 0 open issues, last pushed Apr 12, 2026. [Awesome-Prompt-Engineering](https://discord.gg/m88xfYMbK6) has 6.2k stars, 734 forks, and 94 open issues, last pushed Jul 27, 2026. Figures are from public GitHub metadata via [promptext's repository](https://github.com/1broseidon/promptext) and [Awesome-Prompt-Engineering's repository](https://github.com/promptslab/Awesome-Prompt-Engineering). | | [promptext](/tools/1broseidon-promptext.md) | [Awesome-Prompt-Engineering](/tools/promptslab-awesome-prompt-engineering.md) | | --- | --- | --- | | Tagline | Smart code context extractor for AI assistants | Hand-curated resources for Prompt Engineering focusing on Generative Pre-trained Transformers | | Stars | 22 | 6,197 | | Forks | 1 | 734 | | Open issues | 0 | 94 | | Language | Go | TypeScript | | Adopt for | For developers seeking a tool to streamline AI interaction with codebases via context extraction, promptext stands out for its Go-centric design and CLI focus. | Awesome-Prompt-Engineering curates resources tailored for GPT, ChatGPT, PaLM prompt engineering in TypeScript under Apache-2.0 license. | | Persona | - | - | | Runtime | - | - | | License | The MIT License entails permissive terms under which developers can use, modify, and distribute the software. | Apache-2.0 | | Categories | Developer Tools | Developer Tools, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [promptext](/tools/1broseidon-promptext.md) | [Awesome-Prompt-Engineering](/tools/promptslab-awesome-prompt-engineering.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Very active (96%) | | Days since push | 111d | 0d | | Open issues (now) | 0 | 94 | | Owner type | User | Organization | | Full report | [trust report](/tools/1broseidon-promptext/trust.md) | [trust report](/tools/promptslab-awesome-prompt-engineering/trust.md) | ## Decision facts: promptext - **Pricing:** freemium - promptext is freely available under the MIT license. It does not directly charge for usage but potential costs might arise from integrating it into larger commercial products. - **Requirements:** promptext requires either an existing Go installation (version 1.19+) or uses one-off scripts for installation on macOS/Linux and Windows.; A compatible command-line environment is a must since promptext operates primarily through the command line. - **Adopt for:** For developers seeking a tool to streamline AI interaction with codebases via context extraction, promptext stands out for its Go-centric design and CLI focus. - **License detail:** The MIT License entails permissive terms under which developers can use, modify, and distribute the software. ## Decision facts: Awesome-Prompt-Engineering - **Adopt for:** Awesome-Prompt-Engineering curates resources tailored for GPT, ChatGPT, PaLM prompt engineering in TypeScript under Apache-2.0 license. ## Choose when ### Choose promptext if… - promptext is primarily Go; Awesome-Prompt-Engineering is TypeScript. - License: promptext is MIT, Awesome-Prompt-Engineering is Apache-2.0. - Pricing: promptext is freely available under the MIT license. It does not directly charge for usage but potential costs might arise from integrating it into larger commercial products.. - Requirements: promptext requires either an existing Go installation (version 1.19+) or uses one-off scripts for installation on macOS/Linux and Windows.; A compatible command-line environment is a must since promptext operates primarily through the command line.. - Tags unique to promptext: ai-tools, code-analysis, go. - When you work in a Go (golang) project environment where quick, efficient code context extraction is required. ### Choose Awesome-Prompt-Engineering if… - Awesome-Prompt-Engineering is primarily TypeScript; promptext is Go. - License: Awesome-Prompt-Engineering is Apache-2.0, promptext is MIT. - Tags unique to Awesome-Prompt-Engineering: chatgpt, deep-learning, few-shot-learning, gpt. - Also covers Model Training. - You need focused materials on GPT and related models for prompt engineering ## When NOT to use promptext - In projects heavily reliant on languages other than Go, as the support for extracting contexts from non-Go files is limited. - If your development setup does not allow for CLI operations. promptext's primary mode of operation is through its command-line interface. ## When NOT to use Awesome-Prompt-Engineering - The project requires languages other than TypeScript - Resource is about areas outside of GPT, ChatGPT, PaLM prompt engineering ## Common questions ### What is the difference between promptext and Awesome-Prompt-Engineering? promptext: Smart code context extractor for AI assistants. Awesome-Prompt-Engineering: Hand-curated resources for Prompt Engineering focusing on Generative Pre-trained Transformers. See the comparison table for live GitHub stats and shared categories. ### When should I choose promptext over Awesome-Prompt-Engineering? Choose promptext over Awesome-Prompt-Engineering when promptext is primarily Go; Awesome-Prompt-Engineering is TypeScript; License: promptext is MIT, Awesome-Prompt-Engineering is Apache-2.0; Pricing: promptext is freely available under the MIT license. It does not directly charge for usage but potential costs might arise from integrating it into larger commercial products.; Requirements: promptext requires either an existing Go installation (version 1.19+) or uses one-off scripts for installation on macOS/Linux and Windows.; A compatible command-line environment is a must since promptext operates primarily through the command line.; Tags unique to promptext: ai-tools, code-analysis, go; When you work in a Go (golang) project environment where quick, efficient code context extraction is required. ### When should I choose Awesome-Prompt-Engineering over promptext? Choose Awesome-Prompt-Engineering over promptext when Awesome-Prompt-Engineering is primarily TypeScript; promptext is Go; License: Awesome-Prompt-Engineering is Apache-2.0, promptext is MIT; Tags unique to Awesome-Prompt-Engineering: chatgpt, deep-learning, few-shot-learning, gpt; Also covers Model Training; You need focused materials on GPT and related models for prompt engineering. ### When should I avoid promptext? In projects heavily reliant on languages other than Go, as the support for extracting contexts from non-Go files is limited. If your development setup does not allow for CLI operations. promptext's primary mode of operation is through its command-line interface. ### When should I avoid Awesome-Prompt-Engineering? The project requires languages other than TypeScript Resource is about areas outside of GPT, ChatGPT, PaLM prompt engineering ### Is promptext or Awesome-Prompt-Engineering more popular on GitHub? Awesome-Prompt-Engineering has more GitHub stars (6,197 vs 22). Stars measure visibility, not whether either tool fits your constraints. ### Are promptext and Awesome-Prompt-Engineering open source? Yes - both are open-source projects on GitHub (promptext: MIT, Awesome-Prompt-Engineering: Apache-2.0). ### Where can I find alternatives to promptext or Awesome-Prompt-Engineering? GraphCanon lists graph-backed alternatives at [promptext alternatives](/tools/1broseidon-promptext/alternatives) and [Awesome-Prompt-Engineering alternatives](/tools/promptslab-awesome-prompt-engineering/alternatives) ([promptext markdown twin](/tools/1broseidon-promptext/alternatives.md), [Awesome-Prompt-Engineering markdown twin](/tools/promptslab-awesome-prompt-engineering/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/1broseidon-promptext-vs-promptslab-awesome-prompt-engineering.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, promptext or Awesome-Prompt-Engineering? promptext: Slowing. Awesome-Prompt-Engineering: 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 promptext and Awesome-Prompt-Engineering? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [promptext trust report](/tools/1broseidon-promptext/trust); [Awesome-Prompt-Engineering trust report](/tools/promptslab-awesome-prompt-engineering/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=1broseidon-promptext`](/api/graphcanon/graph?tool=1broseidon-promptext) - 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/_