REPOGEO REPORT · LITE

reasoning-survey/Awesome-Reasoning-Foundation-Models

Default branch main · commit 1b1a1402 · scanned 6/2/2026, 11:06:53 AM

GitHub: 654 stars · 61 forks

AI VISIBILITY SCORE

22 /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

1 / 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 reasoning-survey/Awesome-Reasoning-Foundation-Models, 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 README's H1 to clarify it's a curated list/survey
Why:
CURRENT
```
# Awesome-Reasoning-Foundation-Models
```
COPY-PASTE FIX
```
# Awesome-Reasoning-Foundation-Models: A Curated List of Papers and Benchmarks
```
mediumhomepage#2
Add a homepage URL to the repository's About section
Why:
COPY-PASTE FIX
```
https://doi.org/10.5281/zenodo.10298864
```

lowtopics#3

Add topics to explicitly mark the repository as an 'awesome list' or 'survey'

Why:

CURRENT

foundation-models, llm, llm-reasoning, multimodal, reasoning, reasoning-agent, reasoning-language-models

COPY-PASTE FIX

awesome-list, foundation-models, llm, llm-reasoning, multimodal, reasoning, reasoning-agent, reasoning-language-models, survey-paper

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 reasoning-survey/Awesome-Reasoning-Foundation-Models

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

OpenAI GPT-4

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

OpenAI GPT-4 · recommended 2×
Google PaLM 2 / Gemini · recommended 1×
meta-llama/llama · recommended 1×
tatsu-lab/stanford_alpaca · recommended 1×
lmsys/vicuna · recommended 1×

CATEGORY QUERY
Seeking recent advancements and benchmarks in improving reasoning capabilities of large AI models.
you: not recommended
AI recommended (in order):
1. Google PaLM 2 / Gemini
2. OpenAI GPT-4
3. Meta LLaMA 2 (meta-llama/llama)
4. Alpaca (tatsu-lab/stanford_alpaca)
5. Vicuna (lmsys/vicuna)
6. DeepMind AlphaCode 2
7. MATH dataset (hendrycks/math)
8. GSM8K (openai/grade-school-math)
9. Big-Bench Hard (BBH) (google/BIG-bench)
10. ARC (AI2 Reasoning Challenge) (allenai/arc)
11. MMLU (Massive Multitask Language Understanding) (hendrycks/test)
AI recommended 11 alternatives but never named reasoning-survey/Awesome-Reasoning-Foundation-Models. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are effective techniques for developing autonomous agents with advanced reasoning skills?
you: not recommended
AI recommended (in order):
1. Prolog
2. CLIPS
3. OWL
4. Apache Jena
5. Protégé
6. Soar
7. ACT-R
8. Stable Baselines3
9. Gymnasium
10. Ray RLlib
11. OpenAI GPT-4
12. GPT-3.5 Turbo
13. LangChain
AI recommended 13 alternatives but never named reasoning-survey/Awesome-Reasoning-Foundation-Models. 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 reasoning-survey/Awesome-Reasoning-Foundation-Models?
pass
AI did not name reasoning-survey/Awesome-Reasoning-Foundation-Models — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts reasoning-survey/Awesome-Reasoning-Foundation-Models in production, what risks or prerequisites should they evaluate first?
pass
AI named reasoning-survey/Awesome-Reasoning-Foundation-Models 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 reasoning-survey/Awesome-Reasoning-Foundation-Models solve, and who is the primary audience?
pass
AI did not name reasoning-survey/Awesome-Reasoning-Foundation-Models — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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MARKDOWN (README)

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