---
title: "llm-lobbyist vs awesome-LLM-resources"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/johnnay-llm-lobbyist-vs-wangrongsheng-awesome-llm-resources"
tools: ["johnnay-llm-lobbyist", "wangrongsheng-awesome-llm-resources"]
---

# llm-lobbyist vs awesome-LLM-resources

*GraphCanon updated Aug 17, 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 awesome-LLM-resources if awesome-LLM-resources offers a curated and comprehensive list of resources related to Large Language Models (LLMs), including materials for specialized areas like RAG (Retrieval-Augmented Generation) and agentic RL, as a.

[llm-lobbyist](https://github.com/JohnNay/llm-lobbyist) reports 174 GitHub stars, 14 forks, and 0 open issues, last pushed Jan 13, 2023. [awesome-LLM-resources](https://github.com/WangRongsheng/awesome-LLM-resources) has 8.8k stars, 950 forks, and 23 open issues, last pushed Aug 14, 2026. Figures are from public GitHub metadata via [llm-lobbyist's repository](https://github.com/JohnNay/llm-lobbyist) and [awesome-LLM-resources's repository](https://github.com/WangRongsheng/awesome-LLM-resources).

| | [llm-lobbyist](/tools/johnnay-llm-lobbyist.md) | [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) |
| --- | --- | --- |
| Tagline | Code for research on large language models conducting corporate lobbying activities. | Summary of the world's best LLM resources. |
| Stars | 174 | 8,845 |
| Forks | 14 | 950 |
| Open issues | 0 | 23 |
| Language | 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. | awesome-LLM-resources offers a curated and comprehensive list of resources related to Large Language Models (LLMs), including materials for specialized areas like RAG (Retrieval-Augmented Generation) and agentic RL, as a |
| Persona | - | - |
| Runtime | - | - |
| License | - | Apache-2.0 |
| Categories | Evaluation & Observability, Model Training | AI Agents, Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [llm-lobbyist](/tools/johnnay-llm-lobbyist.md) | [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) |
| --- | --- | --- |
| Maintenance | Dormant (18%) | Very active (96%) |
| Days since push | 1310d | 2d |
| Open issues (now) | 0 | 23 |
| Stars delta | 0 (30d) | +142 (30d) |
| Open issues delta | 0 (30d) | -13 (30d) |
| Full report | [trust report](/tools/johnnay-llm-lobbyist/trust.md) | [trust report](/tools/wangrongsheng-awesome-llm-resources/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: awesome-LLM-resources

- **Adopt for:** awesome-LLM-resources offers a curated and comprehensive list of resources related to Large Language Models (LLMs), including materials for specialized areas like RAG (Retrieval-Augmented Generation) and agentic RL, as a

## 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.
- Leaner open-issue backlog (0).

### Choose awesome-LLM-resources if…

- Tags unique to awesome-LLM-resources: awesome-list, book, course, large language models.
- Also covers AI Agents, Developer Tools, Inference & Serving, LLM Frameworks.
- - It's ideal when you seek an exhaustive and up-to-date compilation covering extensive knowledge points in LLM technologies.

## 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 awesome-LLM-resources

- - Avoid using this resource if you specifically need detailed step-by-step guides or hands-on tutorials that focus deeply on a single technology rather than broad coverage.
- - It might not be the best choice when you are looking for resources in languages other than English, especially given its extensive English content.

## Common questions

### What is the difference between llm-lobbyist and awesome-LLM-resources?

llm-lobbyist: Code for research on large language models conducting corporate lobbying activities.. awesome-LLM-resources: Summary of the world's best LLM resources.. See the comparison table for live GitHub stats and shared categories.

### When should I choose llm-lobbyist over awesome-LLM-resources?

Choose llm-lobbyist over awesome-LLM-resources 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; Leaner open-issue backlog (0).

### When should I choose awesome-LLM-resources over llm-lobbyist?

Choose awesome-LLM-resources over llm-lobbyist when Tags unique to awesome-LLM-resources: awesome-list, book, course, large language models; Also covers AI Agents, Developer Tools, Inference & Serving, LLM Frameworks; - It's ideal when you seek an exhaustive and up-to-date compilation covering extensive knowledge points in LLM technologies.

### 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 awesome-LLM-resources?

- Avoid using this resource if you specifically need detailed step-by-step guides or hands-on tutorials that focus deeply on a single technology rather than broad coverage. - It might not be the best choice when you are looking for resources in languages other than English, especially given its extensive English content.

### Is llm-lobbyist or awesome-LLM-resources more popular on GitHub?

awesome-LLM-resources has more GitHub stars (8,845 vs 174). Stars measure visibility, not whether either tool fits your constraints.

### Are llm-lobbyist and awesome-LLM-resources open source?

Yes - both are open-source projects on GitHub.

### Where can I find alternatives to llm-lobbyist or awesome-LLM-resources?

GraphCanon lists graph-backed alternatives at [llm-lobbyist alternatives](/tools/johnnay-llm-lobbyist/alternatives) and [awesome-LLM-resources alternatives](/tools/wangrongsheng-awesome-llm-resources/alternatives) ([llm-lobbyist markdown twin](/tools/johnnay-llm-lobbyist/alternatives.md), [awesome-LLM-resources markdown twin](/tools/wangrongsheng-awesome-llm-resources/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-wangrongsheng-awesome-llm-resources.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, llm-lobbyist or awesome-LLM-resources?

llm-lobbyist: Dormant. awesome-LLM-resources: 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 awesome-LLM-resources?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [llm-lobbyist trust report](/tools/johnnay-llm-lobbyist/trust); [awesome-LLM-resources trust report](/tools/wangrongsheng-awesome-llm-resources/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/_