--- title: "SuperPrompt vs awesome" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/neovertex1-superprompt-vs-sindresorhus-awesome" tools: ["neovertex1-superprompt", "sindresorhus-awesome"] --- # SuperPrompt vs awesome *GraphCanon updated Jul 12, 2026* ## Verdict Pick SuperPrompt when tags unique to SuperPrompt: ai, ml, prompt-engineering, prompts; pick awesome when tags unique to awesome: awesome, awesome-list, lists, resources. [SuperPrompt](https://github.com/NeoVertex1/SuperPrompt) reports 6.4k GitHub stars, 574 forks, and 12 open issues, last pushed Apr 26, 2026. [awesome](https://github.com/sindresorhus/awesome) has 484k stars, 36k forks, and 92 open issues, last pushed Jun 30, 2026. Figures are from public GitHub metadata via [SuperPrompt's repository](https://github.com/NeoVertex1/SuperPrompt) and [awesome's repository](https://github.com/sindresorhus/awesome). | | [SuperPrompt](/tools/neovertex1-superprompt.md) | [awesome](/tools/sindresorhus-awesome.md) | | --- | --- | --- | | Tagline | SuperPrompt is an attempt to engineer prompts that might help us understand AI agents. | 😎 Awesome lists about all kinds of interesting topics | | Stars | 6,419 | 484,026 | | Forks | 574 | 35,799 | | Open issues | 12 | 92 | | Language | - | - | | Adopt for | - | A curated collection of resources on a variety of technological topics, emphasizing hardware and robotics. | | Persona | - | - | | Runtime | - | - | | License | - | CC0-1.0 | | Categories | AI Agents, LLM Frameworks | Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [SuperPrompt](/tools/neovertex1-superprompt.md) | [awesome](/tools/sindresorhus-awesome.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Active (82%) | | Days since push | 75d | 11d | | Open issues (now) | 12 | 92 | | Full report | [trust report](/tools/neovertex1-superprompt/trust.md) | [trust report](/tools/sindresorhus-awesome/trust.md) | ## Decision facts: awesome - **Adopt for:** A curated collection of resources on a variety of technological topics, emphasizing hardware and robotics. ## Choose when ### Choose SuperPrompt if… - Tags unique to SuperPrompt: ai, ml, prompt-engineering, prompts. - Also covers AI Agents, LLM Frameworks. - Leaner open-issue backlog (12). ### Choose awesome if… - Tags unique to awesome: awesome, awesome-list, lists, resources. - Also covers Developer Tools. - When you need well-organized access to diverse technical subjects from IoT to robotics ## When NOT to use SuperPrompt - 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. ## When NOT to use awesome - If seeking specific coding frameworks or libraries for software development rather than hardware-focused resources - In scenarios requiring real-time interactive support or forums, as the content is static lists without active discussion ## Common questions ### What is the difference between SuperPrompt and awesome? SuperPrompt: SuperPrompt is an attempt to engineer prompts that might help us understand AI agents.. awesome: 😎 Awesome lists about all kinds of interesting topics. See the comparison table for live GitHub stats and shared categories. ### When should I choose SuperPrompt over awesome? Choose SuperPrompt over awesome when Tags unique to SuperPrompt: ai, ml, prompt-engineering, prompts; Also covers AI Agents, LLM Frameworks; Leaner open-issue backlog (12). ### When should I choose awesome over SuperPrompt? Choose awesome over SuperPrompt when Tags unique to awesome: awesome, awesome-list, lists, resources; Also covers Developer Tools; When you need well-organized access to diverse technical subjects from IoT to robotics. ### When should I avoid SuperPrompt? 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. ### When should I avoid awesome? If seeking specific coding frameworks or libraries for software development rather than hardware-focused resources In scenarios requiring real-time interactive support or forums, as the content is static lists without active discussion ### Is SuperPrompt or awesome more popular on GitHub? awesome has more GitHub stars (484,026 vs 6,419). Stars measure visibility, not whether either tool fits your constraints. ### Are SuperPrompt and awesome open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to SuperPrompt or awesome? GraphCanon lists graph-backed alternatives at [SuperPrompt alternatives](/tools/neovertex1-superprompt/alternatives) and [awesome alternatives](/tools/sindresorhus-awesome/alternatives) ([SuperPrompt markdown twin](/tools/neovertex1-superprompt/alternatives.md), [awesome markdown twin](/tools/sindresorhus-awesome/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/neovertex1-superprompt-vs-sindresorhus-awesome.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, SuperPrompt or awesome? SuperPrompt: Steady. awesome: 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 SuperPrompt and awesome? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [SuperPrompt trust report](/tools/neovertex1-superprompt/trust); [awesome trust report](/tools/sindresorhus-awesome/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=neovertex1-superprompt`](/api/graphcanon/graph?tool=neovertex1-superprompt) - 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/_