REPOGEO REPORT · LITE

dave1010/tree-of-thought-prompting

Default branch main · commit c508ff76 · scanned 6/7/2026, 1:51:43 AM

GitHub: 818 stars · 78 forks

AI VISIBILITY SCORE

28 /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

2 / 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 dave1010/tree-of-thought-prompting, 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 to clarify it's a technique implementation, not an LLM

Why:

CURRENT

The README immediately starts with an abstract about the technique.

COPY-PASTE FIX

Add a sentence or two immediately after the main heading or abstract, explicitly stating: "This repository provides a practical implementation and examples of the Tree-of-Thought (ToT) Prompting technique, designed to enhance the reasoning capabilities of existing Large Language Models like ChatGPT, rather than being an LLM itself or a general-purpose framework."

hightopics#2

Add more specific topics to improve categorization

Why:

CURRENT

large-language-models, llm, prompt-engineering

COPY-PASTE FIX

large-language-models, llm, prompt-engineering, tree-of-thought, tot-prompting, llm-reasoning, ai-prompting-techniques

mediumhomepage#3
Add a homepage URL to the repository metadata
Why:
COPY-PASTE FIX
```
https://doi.org/10.5281/zenodo.10323452
```

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 dave1010/tree-of-thought-prompting

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 5 of 2 queries

COMPETITOR LEADERBOARD

OpenAI GPT-4 · recommended 5×
Google Gemini · recommended 4×
langchain-ai/langchain · recommended 4×
GPT-3.5 Turbo · recommended 3×
Anthropic Claude 3 · recommended 3×

CATEGORY QUERY
How to improve large language model reasoning for complex, multi-step questions?
you: not recommended
AI recommended (in order):
1. OpenAI GPT-4
2. GPT-3.5 Turbo
3. Anthropic Claude 3
4. Google Gemini
5. Hugging Face Transformers (huggingface/transformers)
6. OpenAI GPT-4
7. GPT-3.5 Turbo
8. Anthropic Claude 3
9. Google Gemini
10. LangChain (langchain-ai/langchain)
11. LlamaIndex (run-llama/llama_index)
12. OpenAI GPT-4
13. Anthropic Claude 3
14. networkx (networkx/networkx)
15. LangChain (langchain-ai/langchain)
16. LlamaIndex (run-llama/llama_index)
17. Pinecone
18. Weaviate (weaviate/weaviate)
19. ChromaDB (chroma-core/chroma)
20. OpenAI GPT-4
21. GPT-3.5 Turbo
22. Google Gemini
23. OpenAI GPT-4
24. Google Gemini
25. LangChain Agents (langchain-ai/langchain)
26. LlamaIndex Agents (run-llama/llama_index)
27. OpenAI Fine-tuning API
28. Hugging Face Transformers (huggingface/transformers)
29. PyTorch (pytorch/pytorch)
30. TensorFlow (tensorflow/tensorflow)
31. Google Cloud Vertex AI
32. LangChain Agents (langchain-ai/langchain)
33. CrewAI (joaomdmoura/crewAI)
34. GPT-4
35. Claude 3
36. Gemini
AI recommended 36 alternatives but never named dave1010/tree-of-thought-prompting. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are advanced prompting techniques to enhance LLM capabilities beyond chain-of-thought?
you: not recommended
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 dave1010/tree-of-thought-prompting?
pass
AI named dave1010/tree-of-thought-prompting explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts dave1010/tree-of-thought-prompting in production, what risks or prerequisites should they evaluate first?
pass
AI named dave1010/tree-of-thought-prompting 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 dave1010/tree-of-thought-prompting solve, and who is the primary audience?
pass
AI did not name dave1010/tree-of-thought-prompting — 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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dave1010/tree-of-thought-prompting — 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