RRepoGEO

REPOGEO REPORT · LITE

kyegomez/tree-of-thoughts

Default branch main · commit b6197795 · scanned 5/23/2026, 12:41:57 PM

GitHub: 4,577 stars · 375 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
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 kyegomez/tree-of-thoughts, 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

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

OVERALL DIRECTION
  • mediumtopics#1
    Add more specific topics related to LLM reasoning frameworks and structured prompting.

    Why:

    CURRENT
    artificial-intelligence, chatgpt, deep-learning, gpt4, multimodal, prompt, prompt-engineering, prompt-learning, prompt-tuning
    COPY-PASTE FIX
    artificial-intelligence, chatgpt, deep-learning, gpt4, multimodal, prompt, prompt-engineering, prompt-learning, prompt-tuning, llm-reasoning, tree-of-thoughts, structured-prompting, python-library
  • lowreadme#2
    Add a 'Why Choose Tree of Thoughts?' or 'Comparison' section to the README.

    Why:

    COPY-PASTE FIX
    Add a new section to the README, for example: '## Why Choose Tree of Thoughts? While frameworks like LangChain and LlamaIndex offer broad LLM orchestration, `kyegomez/tree-of-thoughts` provides a dedicated, plug-and-play Python implementation specifically for the Tree of Thoughts reasoning framework. This allows developers to directly integrate advanced, deliberate problem-solving capabilities into their LLM applications, going beyond basic prompting or Chain-of-Thought methods.'

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 kyegomez/tree-of-thoughts
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. GSM8K · recommended 1×
  4. MATH · recommended 1×
  5. Big-Bench Hard · recommended 1×
  • CATEGORY QUERY
    How can I enhance large language model reasoning capabilities for complex problem-solving tasks?
    you: not recommended
    AI recommended (in order):
    1. GSM8K
    2. MATH
    3. Big-Bench Hard
    4. ARC
    5. Chain-of-Thought (CoT) Prompting
    6. Tree-of-Thought (ToT) Prompting
    7. Self-Consistency Decoding
    8. Program-Aided Language Models (PAL)
    9. LangChain
    10. LlamaIndex
    11. Wolfram Alpha
    12. Google Search API
    13. Bing Search API
    14. Reinforcement Learning from Human Feedback (RLHF)
    15. Reinforcement Learning from AI Feedback (RLAIF)
    16. Mixtral 8x7B
    17. Claude 2.1
    18. GPT-4 Turbo

    AI recommended 18 alternatives but never named kyegomez/tree-of-thoughts. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a Python library to boost LLM reasoning for complex tasks via structured prompting.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Instructor
    4. Guidance
    5. Marvin
    6. Outlines

    AI recommended 6 alternatives but never named kyegomez/tree-of-thoughts. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 kyegomez/tree-of-thoughts?
    pass
    AI named kyegomez/tree-of-thoughts explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts kyegomez/tree-of-thoughts in production, what risks or prerequisites should they evaluate first?
    pass
    AI named kyegomez/tree-of-thoughts 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 kyegomez/tree-of-thoughts solve, and who is the primary audience?
    pass
    AI named kyegomez/tree-of-thoughts explicitly

    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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kyegomez/tree-of-thoughts — 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