--- title: "Awesome-Code-LLM vs academic-research-skills" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/huybery-awesome-code-llm-vs-imbad0202-academic-research-skills" tools: ["huybery-awesome-code-llm", "imbad0202-academic-research-skills"] --- # Awesome-Code-LLM vs academic-research-skills *GraphCanon updated Jul 11, 2026* ## Verdict Pick Awesome-Code-LLM when license: Awesome-Code-LLM is MIT, academic-research-skills is Other; pick academic-research-skills when license: academic-research-skills is Other, Awesome-Code-LLM is MIT. [Awesome-Code-LLM](https://github.com/huybery/Awesome-Code-LLM) reports 1.3k GitHub stars, 74 forks, and 3 open issues, last pushed Dec 10, 2024. [academic-research-skills](https://buymeacoffee.com/crucify020v) has 37k stars, 3.0k forks, and 9 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [Awesome-Code-LLM's repository](https://github.com/huybery/Awesome-Code-LLM) and [academic-research-skills's repository](https://github.com/Imbad0202/academic-research-skills). | | [Awesome-Code-LLM](/tools/huybery-awesome-code-llm.md) | [academic-research-skills](/tools/imbad0202-academic-research-skills.md) | | --- | --- | --- | | Tagline | 👨💻 An awesome and curated list of best code-LLM for research. | Academic Research Skills for Claude Code: research → write → review → revise → finalize | | Stars | 1,288 | 37,300 | | Forks | 74 | 3,043 | | Open issues | 3 | 9 | | Language | - | Python | | Adopt for | Awesome-Code-LLM is a curated repository focused on code-focused large language models (code-LLMs), providing insights into top-performing models, evaluation toolkits, and research papers. | - | | Persona | - | - | | Runtime | - | - | | License | MIT License: Permissive open-source license that allows usage in virtually any project with little restrictions. | Other | | Categories | Evaluation & Observability, LLM Frameworks | Data & Retrieval, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Awesome-Code-LLM](/tools/huybery-awesome-code-llm.md) | [academic-research-skills](/tools/imbad0202-academic-research-skills.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 578d | 0d | | Open issues (now) | 3 | 9 | | Full report | [trust report](/tools/huybery-awesome-code-llm/trust.md) | [trust report](/tools/imbad0202-academic-research-skills/trust.md) | ## Decision facts: Awesome-Code-LLM - **Requirements:** No specific requirements to use the repository for reference or evaluation, but contributions may involve technical knowledge and familiarity with code-LLMs. - **Adopt for:** Awesome-Code-LLM is a curated repository focused on code-focused large language models (code-LLMs), providing insights into top-performing models, evaluation toolkits, and research papers. - **License detail:** MIT License: Permissive open-source license that allows usage in virtually any project with little restrictions. ## Choose when ### Choose Awesome-Code-LLM if… - License: Awesome-Code-LLM is MIT, academic-research-skills is Other. - Requirements: No specific requirements to use the repository for reference or evaluation, but contributions may involve technical knowledge and familiarity with code-LLMs.. - Tags unique to Awesome-Code-LLM: awesome, code-generation, large-language-models. - Also covers Evaluation & Observability. - When you need a comprehensive list of state-of-the-art code generation LLMs with performance metrics such as HumanEval. ### Choose academic-research-skills if… - License: academic-research-skills is Other, Awesome-Code-LLM is MIT. - Tags unique to academic-research-skills: academic-pipeline, academic-writing, ai-research, claude. - Also covers Data & Retrieval. ## When NOT to use Awesome-Code-LLM - When looking for a tool that provides pre-trained models with built-in APIs or services, as Awesome-Code-LLM is primarily a directory/collection of information without direct service provision. - If you require real-time interactive use-cases and need immediate API access to LLMs; this repository does not offer such functionality. - In scenarios where you need a single end-to-end solution for training your own code generation models, as the platform is focused on aggregating third-party resources and research rather than offering ## When NOT to use academic-research-skills - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between Awesome-Code-LLM and academic-research-skills? Awesome-Code-LLM: 👨💻 An awesome and curated list of best code-LLM for research.. academic-research-skills: Academic Research Skills for Claude Code: research → write → review → revise → finalize. See the comparison table for live GitHub stats and shared categories. ### When should I choose Awesome-Code-LLM over academic-research-skills? Choose Awesome-Code-LLM over academic-research-skills when License: Awesome-Code-LLM is MIT, academic-research-skills is Other; Requirements: No specific requirements to use the repository for reference or evaluation, but contributions may involve technical knowledge and familiarity with code-LLMs.; Tags unique to Awesome-Code-LLM: awesome, code-generation, large-language-models; Also covers Evaluation & Observability; When you need a comprehensive list of state-of-the-art code generation LLMs with performance metrics such as HumanEval. ### When should I choose academic-research-skills over Awesome-Code-LLM? Choose academic-research-skills over Awesome-Code-LLM when License: academic-research-skills is Other, Awesome-Code-LLM is MIT; Tags unique to academic-research-skills: academic-pipeline, academic-writing, ai-research, claude; Also covers Data & Retrieval. ### When should I avoid Awesome-Code-LLM? When looking for a tool that provides pre-trained models with built-in APIs or services, as Awesome-Code-LLM is primarily a directory/collection of information without direct service provision. If you require real-time interactive use-cases and need immediate API access to LLMs; this repository does not offer such functionality. In scenarios where you need a single end-to-end solution for training your own code generation models, as the platform is focused on aggregating third-party resources and research rather than offering ### When should I avoid academic-research-skills? Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is Awesome-Code-LLM or academic-research-skills more popular on GitHub? academic-research-skills has more GitHub stars (37,300 vs 1,288). Stars measure visibility, not whether either tool fits your constraints. ### Are Awesome-Code-LLM and academic-research-skills open source? Yes - both are open-source projects on GitHub (Awesome-Code-LLM: MIT, academic-research-skills: Other). ### Where can I find alternatives to Awesome-Code-LLM or academic-research-skills? GraphCanon lists graph-backed alternatives at [Awesome-Code-LLM alternatives](/tools/huybery-awesome-code-llm/alternatives) and [academic-research-skills alternatives](/tools/imbad0202-academic-research-skills/alternatives) ([Awesome-Code-LLM markdown twin](/tools/huybery-awesome-code-llm/alternatives.md), [academic-research-skills markdown twin](/tools/imbad0202-academic-research-skills/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/huybery-awesome-code-llm-vs-imbad0202-academic-research-skills.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Awesome-Code-LLM or academic-research-skills? Awesome-Code-LLM: Dormant. academic-research-skills: 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 Awesome-Code-LLM and academic-research-skills? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Awesome-Code-LLM trust report](/tools/huybery-awesome-code-llm/trust); [academic-research-skills trust report](/tools/imbad0202-academic-research-skills/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=huybery-awesome-code-llm`](/api/graphcanon/graph?tool=huybery-awesome-code-llm) - 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/_