RRepoGEO

REPOGEO REPORT · LITE

ZongqianLi/ReasonGraph

Default branch main · commit ac3bab27 · scanned 6/15/2026, 12:48:03 AM

GitHub: 511 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 ZongqianLi/ReasonGraph, 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
  • highlicense#1
    Add a LICENSE file to the repository root

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root with the text of a permissive open-source license, such as the MIT License.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    llm, reasoning, visualization, graph-visualization, acl2025, nlp, ai-debugging, interpretability, large-language-models
  • highhomepage#3
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    https://huggingface.co/spaces/ZongqianLi/ReasonGraph

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 ZongqianLi/ReasonGraph
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Voyager
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Voyager · recommended 1×
  2. LangSmith · recommended 1×
  3. OpenAI Playground/API Logs · recommended 1×
  4. Graphviz · recommended 1×
  5. Mermaid.js · recommended 1×
  • CATEGORY QUERY
    I need a tool to visualize complex reasoning paths generated by large language models.
    you: not recommended
    AI recommended (in order):
    1. Voyager
    2. LangSmith
    3. OpenAI Playground/API Logs
    4. Graphviz
    5. Mermaid.js
    6. D3.js
    7. React Flow

    AI recommended 7 alternatives but never named ZongqianLi/ReasonGraph. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I better understand and debug the inference steps of my AI reasoning models?
    you: not recommended
    AI recommended (in order):
    1. InterpretML
    2. SHAP
    3. LIME
    4. TensorBoard
    5. What-If Tool
    6. TF-Explain
    7. Captum
    8. ELI5
    9. DeepExplain

    AI recommended 9 alternatives but never named ZongqianLi/ReasonGraph. 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 ZongqianLi/ReasonGraph?
    pass
    AI named ZongqianLi/ReasonGraph explicitly

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

  • If a team adopts ZongqianLi/ReasonGraph in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ZongqianLi/ReasonGraph 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 ZongqianLi/ReasonGraph solve, and who is the primary audience?
    pass
    AI named ZongqianLi/ReasonGraph 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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MARKDOWN (README)
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HTML
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ZongqianLi/ReasonGraph — 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