RRepoGEO

REPOGEO REPORT · LITE

THUDM/ReST-MCTS

Default branch main · commit 2d5f488c · scanned 5/31/2026, 9:18:00 PM

GitHub: 706 stars · 49 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 THUDM/ReST-MCTS, 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
  • hightopics#1
    Add specific topics to the repository metadata

    Why:

    COPY-PASTE FIX
    llm, large-language-models, self-training, reinforcement-learning, mcts, monte-carlo-tree-search, neurips-2024, ai-reasoning, process-reward
  • highhomepage#2
    Add the project homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://rest-mcts.github.io/
  • highlicense#3
    Add a LICENSE file to clarify usage rights

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the text of the MIT License.

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 THUDM/ReST-MCTS
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Anthropic's Constitutional AI
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Anthropic's Constitutional AI · recommended 1×
  2. huggingface/transformers · recommended 1×
  3. OpenAI's GPT-3.5/4 · recommended 1×
  4. scikit-learn/scikit-learn · recommended 1×
  5. Google's PaLM 2 / Gemini · recommended 1×
  • CATEGORY QUERY
    How to self-train large language models without extensive human feedback on intermediate steps?
    you: not recommended
    AI recommended (in order):
    1. Anthropic's Constitutional AI
    2. Hugging Face Transformers library (huggingface/transformers)
    3. OpenAI's GPT-3.5/4
    4. Scikit-learn (scikit-learn/scikit-learn)
    5. Google's PaLM 2 / Gemini
    6. PyTorch Lightning (Lightning-AI/lightning)
    7. TensorFlow Keras (tensorflow/tensorflow)

    AI recommended 7 alternatives but never named THUDM/ReST-MCTS. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What methods exist for improving LLM reasoning by automatically generating high-quality thought processes?
    you: not recommended
    AI recommended (in order):
    1. Constitutional AI
    2. Toolformer
    3. LangChain
    4. LlamaIndex
    5. Reflexion

    AI recommended 5 alternatives but never named THUDM/ReST-MCTS. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 THUDM/ReST-MCTS?
    pass
    AI named THUDM/ReST-MCTS explicitly

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

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

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

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THUDM/ReST-MCTS — 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