REPOGEO REPORT · LITE

thinkwee/AgentsMeetRL

Default branch main · commit 62137555 · scanned 5/23/2026, 11:12:57 PM

GitHub: 1,415 stars · 55 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

35 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

3 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface thinkwee/AgentsMeetRL, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

highreadme#1

Reposition the README's opening to clearly state it's an awesome list of projects

Why:

CURRENT

# When LLM Agents Meet Reinforcement Learning

**AgentsMeetRL** is an awesome list that summarizes **open-source repositories** for training LLM Agents using reinforcement learning:

COPY-PASTE FIX

# Awesome List: When LLM Agents Meet Reinforcement Learning

**AgentsMeetRL** is the definitive awesome list summarizing **open-source repositories** for training LLM Agents using reinforcement learning:

highlicense#2

Add a standard open-source LICENSE file

Why:

CURRENT

(no LICENSE file detected)

COPY-PASTE FIX

(Choose and add a standard open-source license file, e.g., MIT, Apache-2.0, or GPL-3.0, to the repository root.)

mediumtopics#3

Add 'curated-list' topic to reinforce the repo's nature

Why:

CURRENT

agent, agentic-ai, agentic-coding, agentic-workflow, awesome-list, large-language-model, llm, llm-age, multiagent, reinforcement, rlhf, rlvr, tool-learning

COPY-PASTE FIX

agent, agentic-ai, agentic-coding, agentic-workflow, awesome-list, curated-list, large-language-model, llm, llm-age, multiagent, reinforcement, rlhf, rlvr, tool-learning

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface thinkwee/AgentsMeetRL

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

LangChain

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

LangChain · recommended 1×
huggingface/agents · recommended 1×
TRL · recommended 1×
DeepSpeed-Chat · recommended 1×
MetaGPT · recommended 1×

CATEGORY QUERY
Where can I find open-source projects combining large language model agents with reinforcement learning?
you: not recommended
AI recommended (in order):
1. LangChain
2. Hugging Face Transformers Agents (huggingface/agents)
3. TRL
4. DeepSpeed-Chat
5. MetaGPT
6. BabyAGI
7. Auto-GPT
8. OpenAI Gym
9. Farama Foundation Gymnasium
10. MiniWoB++
AI recommended 10 alternatives but never named thinkwee/AgentsMeetRL. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are the best reinforcement learning frameworks for training multi-turn LLM agents with tool use?
you: not recommended
AI recommended (in order):
1. RLlib (ray-project/ray)
2. Tianshou (thu-ml/tianshou)
3. Stable Baselines3 (DLR-RM/stable-baselines3)
4. Hugging Face Transformers (huggingface/transformers)
5. CleanRL (vwxyzjn/cleanrl)
6. Acme (deepmind/acme)
7. OpenAI Gym (openai/gym)
8. Farama Gymnasium (Farama-Foundation/Gymnasium)
AI recommended 8 alternatives but never named thinkwee/AgentsMeetRL. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
warn
Suggestion:
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of thinkwee/AgentsMeetRL?
pass
AI named thinkwee/AgentsMeetRL explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts thinkwee/AgentsMeetRL in production, what risks or prerequisites should they evaluate first?
pass
AI named thinkwee/AgentsMeetRL explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo thinkwee/AgentsMeetRL solve, and who is the primary audience?
pass
AI named thinkwee/AgentsMeetRL explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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MARKDOWN (README)

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thinkwee/AgentsMeetRL — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite