RRepoGEO

REPOGEO REPORT · LITE

mintisan/awesome-kan

Default branch main · commit 831dbd5d · scanned 5/14/2026, 8:53:17 PM

GitHub: 3,225 stars · 307 forks

AI VISIBILITY SCORE
23 /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
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 mintisan/awesome-kan, 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
    Clarify README opening to prevent Kanban confusion

    Why:

    CURRENT
    A curated list of awesome libraries, projects, tutorials, papers, and other resources related to Kolmogorov-Arnold Network (KAN). This repository aims to be a comprehensive and organized collection that will help researchers and developers in the world of KAN!
    COPY-PASTE FIX
    A curated list of awesome libraries, projects, tutorials, papers, and other resources related to **Kolmogorov-Arnold Networks (KANs)**. This is *not* about Kanban project management. This repository aims to be a comprehensive and organized collection that will help researchers and developers in the world of KANs!
  • hightopics#2
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    kolmogorov-arnold-networks, kan, neural-networks, machine-learning, deep-learning, awesome-list, research, ai
  • highlicense#3
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT or Apache-2.0) in the repository root to clearly state the terms of use for the content.

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 mintisan/awesome-kan
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
kindness/KAN
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. kindness/KAN · recommended 1×
  2. pykan library · recommended 1×
  3. nflows · recommended 1×
  4. deep-spline-networks · recommended 1×
  5. interpret-ml · recommended 1×
  • CATEGORY QUERY
    Seeking libraries and projects for neural networks inspired by the Kolmogorov-Arnold representation.
    you: not recommended
    AI recommended (in order):
    1. Kolmogorov-Arnold Network (KANs) (kindness/KAN)
    2. pykan library
    3. nflows
    4. deep-spline-networks
    5. interpret-ml
    6. tf-neural-additive-models
    7. pytorch-forecasting
    8. scikit-learn

    AI recommended 8 alternatives but never named mintisan/awesome-kan. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find tutorials and papers on advanced function approximation neural network architectures?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Google Scholar
    3. Distill.pub
    4. NeurIPS
    5. ICLR
    6. Journal of Machine Learning Research
    7. DeepMind
    8. OpenAI

    AI recommended 8 alternatives but never named mintisan/awesome-kan. 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 mintisan/awesome-kan?
    pass
    AI named mintisan/awesome-kan explicitly

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

  • If a team adopts mintisan/awesome-kan in production, what risks or prerequisites should they evaluate first?
    pass
    AI named mintisan/awesome-kan 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 mintisan/awesome-kan solve, and who is the primary audience?
    pass
    AI did not name mintisan/awesome-kan — 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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mintisan/awesome-kan — 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