--- title: "ThoughtSource vs awesome" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/openbiolink-thoughtsource-vs-sindresorhus-awesome" tools: ["openbiolink-thoughtsource", "sindresorhus-awesome"] --- # ThoughtSource vs awesome *GraphCanon updated Jul 12, 2026* ## Verdict Pick ThoughtSource when license: ThoughtSource is MIT, awesome is CC0-1.0; pick awesome when license: awesome is CC0-1.0, ThoughtSource is MIT. [ThoughtSource](https://github.com/OpenBioLink/ThoughtSource) reports 1.0k GitHub stars, 81 forks, and 15 open issues, last pushed Dec 16, 2024. [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 [ThoughtSource's repository](https://github.com/OpenBioLink/ThoughtSource) and [awesome's repository](https://github.com/sindresorhus/awesome). | | [ThoughtSource](/tools/openbiolink-thoughtsource.md) | [awesome](/tools/sindresorhus-awesome.md) | | --- | --- | --- | | Tagline | A central, open resource for data and tools related to chain-of-thought reasoning in large language models. Developed @ Samwald research group: https://samwald.info/ | 😎 Curated list of awesome topics including hardware resources | | Stars | 1,015 | 484,026 | | Forks | 81 | 35,799 | | Open issues | 15 | 92 | | Language | Jupyter Notebook | - | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | MIT | CC0-1.0 | | Categories | LLM Frameworks | LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ThoughtSource](/tools/openbiolink-thoughtsource.md) | [awesome](/tools/sindresorhus-awesome.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Active (82%) | | Days since push | 571d | 11d | | Open issues (now) | 15 | 92 | | Owner type | Organization | User | | Full report | [trust report](/tools/openbiolink-thoughtsource/trust.md) | [trust report](/tools/sindresorhus-awesome/trust.md) | ## Choose when ### Choose ThoughtSource if… - License: ThoughtSource is MIT, awesome is CC0-1.0. - Tags unique to ThoughtSource: dataset, jupyter notebook, machine-learning, natural-language-processing. - Leaner open-issue backlog (15). ### Choose awesome if… - License: awesome is CC0-1.0, ThoughtSource is MIT. - Tags unique to awesome: awesome-list, resources. - More GitHub stars (484k vs 1.0k) - visibility, not fit. ## When NOT to use ThoughtSource - Last GitHub push was 572 days ago (dormant maintenance, Dec 16, 2024). Validate activity before betting a new project on ThoughtSource. - 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 - 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 ThoughtSource and awesome? ThoughtSource: A central, open resource for data and tools related to chain-of-thought reasoning in large language models. Developed @ Samwald research group: https://samwald.info/. awesome: 😎 Curated list of awesome topics including hardware resources. See the comparison table for live GitHub stats and shared categories. ### When should I choose ThoughtSource over awesome? Choose ThoughtSource over awesome when License: ThoughtSource is MIT, awesome is CC0-1.0; Tags unique to ThoughtSource: dataset, jupyter notebook, machine-learning, natural-language-processing; Leaner open-issue backlog (15). ### When should I choose awesome over ThoughtSource? Choose awesome over ThoughtSource when License: awesome is CC0-1.0, ThoughtSource is MIT; Tags unique to awesome: awesome-list, resources; More GitHub stars (484k vs 1.0k) - visibility, not fit. ### When should I avoid ThoughtSource? Last GitHub push was 572 days ago (dormant maintenance, Dec 16, 2024). Validate activity before betting a new project on ThoughtSource. 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? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is ThoughtSource or awesome more popular on GitHub? awesome has more GitHub stars (484,026 vs 1,015). Stars measure visibility, not whether either tool fits your constraints. ### Are ThoughtSource and awesome open source? Yes - both are open-source projects on GitHub (ThoughtSource: MIT, awesome: CC0-1.0). ### Where can I find alternatives to ThoughtSource or awesome? GraphCanon lists graph-backed alternatives at [ThoughtSource alternatives](/tools/openbiolink-thoughtsource/alternatives) and [awesome alternatives](/tools/sindresorhus-awesome/alternatives) ([ThoughtSource markdown twin](/tools/openbiolink-thoughtsource/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/openbiolink-thoughtsource-vs-sindresorhus-awesome.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ThoughtSource or awesome? ThoughtSource: Dormant. 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 ThoughtSource and awesome? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ThoughtSource trust report](/tools/openbiolink-thoughtsource/trust); [awesome trust report](/tools/sindresorhus-awesome/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=openbiolink-thoughtsource`](/api/graphcanon/graph?tool=openbiolink-thoughtsource) - 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/_