--- title: "llms-tools vs awesome-ai-apps" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/petroivaniuk-llms-tools-vs-rohitg00-awesome-ai-apps" tools: ["petroivaniuk-llms-tools", "rohitg00-awesome-ai-apps"] --- # llms-tools vs awesome-ai-apps *GraphCanon updated Aug 12, 2026* ## Verdict Pick llms-tools if covers tools and projects related to large language models with an emphazis on chatbots, LLM evaluation, data science, machine learning, including open-source solutions; pick awesome-ai-apps if awesome-ai-apps offers curated AI application examples with diverse tech stacks including OpenAI, Gemini, and local models. [llms-tools](https://github.com/PetroIvaniuk/llms-tools) reports 321 GitHub stars, 48 forks, and 5 open issues, last pushed Jun 1, 2026. [awesome-ai-apps](https://agenstskills.com) has 817 stars, 174 forks, and 27 open issues, last pushed Feb 10, 2026. Figures are from public GitHub metadata via [llms-tools's repository](https://github.com/PetroIvaniuk/llms-tools) and [awesome-ai-apps's repository](https://github.com/rohitg00/awesome-ai-apps). | | [llms-tools](/tools/petroivaniuk-llms-tools.md) | [awesome-ai-apps](/tools/rohitg00-awesome-ai-apps.md) | | --- | --- | --- | | Tagline | A list of LLMs Tools & Projects | A curated collection of AI Agents and LLM Apps with various tech stacks | | Stars | 321 | 817 | | Forks | 48 | 174 | | Open issues | 5 | 27 | | Language | - | HTML | | Adopt for | Covers tools and projects related to large language models with an emphazis on chatbots, LLM evaluation, data science, machine learning, including open-source solutions. | awesome-ai-apps offers curated AI application examples with diverse tech stacks including OpenAI, Gemini, and local models. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Evaluation & Observability, LLM Frameworks | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [llms-tools](/tools/petroivaniuk-llms-tools.md) | [awesome-ai-apps](/tools/rohitg00-awesome-ai-apps.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Slowing (36%) | | Days since push | 57d | 182d | | Open issues (now) | 5 | 27 | | Full report | [trust report](/tools/petroivaniuk-llms-tools/trust.md) | [trust report](/tools/rohitg00-awesome-ai-apps/trust.md) | ## Decision facts: llms-tools - **Adopt for:** Covers tools and projects related to large language models with an emphazis on chatbots, LLM evaluation, data science, machine learning, including open-source solutions. - **License detail:** Apache-2.0 ## Decision facts: awesome-ai-apps - **Adopt for:** awesome-ai-apps offers curated AI application examples with diverse tech stacks including OpenAI, Gemini, and local models. ## Choose when ### Choose llms-tools if… - Tags unique to llms-tools: chat-bot, chatbots, chatgpt, data-science. - Also covers Evaluation & Observability. - When you need a comprehensive list of resources specifically covering various aspects of developing or evaluating large language models involving chatbot technologies. ### Choose awesome-ai-apps if… - Tags unique to awesome-ai-apps: agents, apps, automation, framework. - Also covers AI Agents. - For exploring real-world implementations of AI agents across different technologies ## When NOT to use llms-tools - Avoid if the focus is on proprietary toolsets, as llms-tools leans towards listing more of its resources under open-source classification. - Not ideal when looking for detailed guides or tutorials to implement specific features, since it does not provide step-by-step instructions but instead a directory of relevant LLM tools. ## When NOT to use awesome-ai-apps - When seeking detailed implementation steps specific to one technology stack - In scenarios demanding a deep dive into proprietary or less publicly-known application codes ## Common questions ### What is the difference between llms-tools and awesome-ai-apps? llms-tools: A list of LLMs Tools & Projects. awesome-ai-apps: A curated collection of AI Agents and LLM Apps with various tech stacks. See the comparison table for live GitHub stats and shared categories. ### When should I choose llms-tools over awesome-ai-apps? Choose llms-tools over awesome-ai-apps when Tags unique to llms-tools: chat-bot, chatbots, chatgpt, data-science; Also covers Evaluation & Observability; When you need a comprehensive list of resources specifically covering various aspects of developing or evaluating large language models involving chatbot technologies. ### When should I choose awesome-ai-apps over llms-tools? Choose awesome-ai-apps over llms-tools when Tags unique to awesome-ai-apps: agents, apps, automation, framework; Also covers AI Agents; For exploring real-world implementations of AI agents across different technologies. ### When should I avoid llms-tools? Avoid if the focus is on proprietary toolsets, as llms-tools leans towards listing more of its resources under open-source classification. Not ideal when looking for detailed guides or tutorials to implement specific features, since it does not provide step-by-step instructions but instead a directory of relevant LLM tools. ### When should I avoid awesome-ai-apps? When seeking detailed implementation steps specific to one technology stack In scenarios demanding a deep dive into proprietary or less publicly-known application codes ### Is llms-tools or awesome-ai-apps more popular on GitHub? awesome-ai-apps has more GitHub stars (817 vs 321). Stars measure visibility, not whether either tool fits your constraints. ### Are llms-tools and awesome-ai-apps open source? Yes - both are open-source projects on GitHub (llms-tools: Apache-2.0, awesome-ai-apps: Apache-2.0). ### Where can I find alternatives to llms-tools or awesome-ai-apps? GraphCanon lists graph-backed alternatives at [llms-tools alternatives](/tools/petroivaniuk-llms-tools/alternatives) and [awesome-ai-apps alternatives](/tools/rohitg00-awesome-ai-apps/alternatives) ([llms-tools markdown twin](/tools/petroivaniuk-llms-tools/alternatives.md), [awesome-ai-apps markdown twin](/tools/rohitg00-awesome-ai-apps/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/petroivaniuk-llms-tools-vs-rohitg00-awesome-ai-apps.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, llms-tools or awesome-ai-apps? llms-tools: Steady. awesome-ai-apps: Slowing. 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 llms-tools and awesome-ai-apps? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [llms-tools trust report](/tools/petroivaniuk-llms-tools/trust); [awesome-ai-apps trust report](/tools/rohitg00-awesome-ai-apps/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=petroivaniuk-llms-tools`](/api/graphcanon/graph?tool=petroivaniuk-llms-tools) - 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/_