--- title: "llm-lobbyist vs LLMForEverybody" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/johnnay-llm-lobbyist-vs-luhengshiwo-llmforeverybody" tools: ["johnnay-llm-lobbyist", "luhengshiwo-llmforeverybody"] --- # llm-lobbyist vs LLMForEverybody *GraphCanon updated Aug 18, 2026* ## Verdict Pick llm-lobbyist if the llm-lobbyist tool specializes in evaluating large language models' efficiency in conducting corporate lobbying activities using Jupyter Notebook and the `text-davinci-003` model; pick LLMForEverybody if lLMForEverybody is a repository primarily focused on sharing knowledge about large language models, with content that includes interview practice, research paper studies (from foundational Transformer papers to more up-t. [llm-lobbyist](https://github.com/JohnNay/llm-lobbyist) reports 174 GitHub stars, 14 forks, and 0 open issues, last pushed Jan 13, 2023. [LLMForEverybody](https://www.learnllm.ai) has 7.2k stars, 662 forks, and 0 open issues, last pushed Aug 17, 2026. Figures are from public GitHub metadata via [llm-lobbyist's repository](https://github.com/JohnNay/llm-lobbyist) and [LLMForEverybody's repository](https://github.com/luhengshiwo/LLMForEverybody). | | [llm-lobbyist](/tools/johnnay-llm-lobbyist.md) | [LLMForEverybody](/tools/luhengshiwo-llmforeverybody.md) | | --- | --- | --- | | Tagline | Code for research on large language models conducting corporate lobbying activities. | LLM knowledge sharing for everyone, essential reading before big model interviews | | Stars | 174 | 7,167 | | Forks | 14 | 662 | | Open issues | 0 | 0 | | Language | Jupyter Notebook | Jupyter Notebook | | Adopt for | The llm-lobbyist tool specializes in evaluating large language models' efficiency in conducting corporate lobbying activities using Jupyter Notebook and the `text-davinci-003` model. | LLMForEverybody is a repository primarily focused on sharing knowledge about large language models, with content that includes interview practice, research paper studies (from foundational Transformer papers to more up-t | | Persona | - | - | | Runtime | - | - | | License | - | Apache-2.0 | | Categories | Evaluation & Observability, Model Training | Evaluation & Observability, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [llm-lobbyist](/tools/johnnay-llm-lobbyist.md) | [LLMForEverybody](/tools/luhengshiwo-llmforeverybody.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 1310d | 1d | | Stars delta | 0 (30d) | +198 (30d) | | Full report | [trust report](/tools/johnnay-llm-lobbyist/trust.md) | [trust report](/tools/luhengshiwo-llmforeverybody/trust.md) | ## Decision facts: llm-lobbyist - **Adopt for:** The llm-lobbyist tool specializes in evaluating large language models' efficiency in conducting corporate lobbying activities using Jupyter Notebook and the `text-davinci-003` model. ## Decision facts: LLMForEverybody - **Adopt for:** LLMForEverybody is a repository primarily focused on sharing knowledge about large language models, with content that includes interview practice, research paper studies (from foundational Transformer papers to more up-t ## Choose when ### Choose llm-lobbyist if… - Tags unique to llm-lobbyist: corporate lobbying, llm-evaluation, text davinci 003. - When you need to assess how well automated systems can determine if legislative proposals are relevant for particular public companies. ### Choose LLMForEverybody if… - Tags unique to LLMForEverybody: agent, interview-practice, learnllm, llm. - Also covers LLM Frameworks. - If you are preparing for job interviews in the field of LLMs or related technologies and want access to practical questions and answers. ## When NOT to use llm-lobbyist - If your scope of work does not involve evaluating or training large language models in a legal policy context. - When you require a tool to analyze or generate content unrelated to legislative relevance, such as technical documentation or creative writing. ## When NOT to use LLMForEverybody - If your learning preference leans towards a different language or if the Chinese-specific resources don't align with your needs. - For individuals looking for comprehensive open-source tools or frameworks to build upon directly; this is more about educational content than concrete implementations. ## Common questions ### What is the difference between llm-lobbyist and LLMForEverybody? llm-lobbyist: Code for research on large language models conducting corporate lobbying activities.. LLMForEverybody: LLM knowledge sharing for everyone, essential reading before big model interviews. See the comparison table for live GitHub stats and shared categories. ### When should I choose llm-lobbyist over LLMForEverybody? Choose llm-lobbyist over LLMForEverybody when Tags unique to llm-lobbyist: corporate lobbying, llm-evaluation, text davinci 003; When you need to assess how well automated systems can determine if legislative proposals are relevant for particular public companies. ### When should I choose LLMForEverybody over llm-lobbyist? Choose LLMForEverybody over llm-lobbyist when Tags unique to LLMForEverybody: agent, interview-practice, learnllm, llm; Also covers LLM Frameworks; If you are preparing for job interviews in the field of LLMs or related technologies and want access to practical questions and answers. ### When should I avoid llm-lobbyist? If your scope of work does not involve evaluating or training large language models in a legal policy context. When you require a tool to analyze or generate content unrelated to legislative relevance, such as technical documentation or creative writing. ### When should I avoid LLMForEverybody? If your learning preference leans towards a different language or if the Chinese-specific resources don't align with your needs. For individuals looking for comprehensive open-source tools or frameworks to build upon directly; this is more about educational content than concrete implementations. ### Is llm-lobbyist or LLMForEverybody more popular on GitHub? LLMForEverybody has more GitHub stars (7,167 vs 174). Stars measure visibility, not whether either tool fits your constraints. ### Are llm-lobbyist and LLMForEverybody open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to llm-lobbyist or LLMForEverybody? GraphCanon lists graph-backed alternatives at [llm-lobbyist alternatives](/tools/johnnay-llm-lobbyist/alternatives) and [LLMForEverybody alternatives](/tools/luhengshiwo-llmforeverybody/alternatives) ([llm-lobbyist markdown twin](/tools/johnnay-llm-lobbyist/alternatives.md), [LLMForEverybody markdown twin](/tools/luhengshiwo-llmforeverybody/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/johnnay-llm-lobbyist-vs-luhengshiwo-llmforeverybody.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, llm-lobbyist or LLMForEverybody? llm-lobbyist: Dormant. LLMForEverybody: 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 llm-lobbyist and LLMForEverybody? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [llm-lobbyist trust report](/tools/johnnay-llm-lobbyist/trust); [LLMForEverybody trust report](/tools/luhengshiwo-llmforeverybody/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=johnnay-llm-lobbyist`](/api/graphcanon/graph?tool=johnnay-llm-lobbyist) - 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/_