RRepoGEO

REPOGEO REPORT · LITE

hijohnnylin/neuronpedia

Default branch main · commit 56364313 · scanned 6/15/2026, 3:56:10 AM

GitHub: 918 stars · 120 forks

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 hijohnnylin/neuronpedia, 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's opening statement to specify LLM neuron focus

    Why:

    CURRENT
    open source interpretability platform
    COPY-PASTE FIX
    A web-based, interactive atlas for visualizing and understanding individual neurons within large language models.
  • hightopics#2
    Add specific topics for LLM neuron interpretability

    Why:

    CURRENT
    ai, interpretability
    COPY-PASTE FIX
    ai, interpretability, llm-interpretability, mechanistic-interpretability, neural-networks, large-language-models, neuron-visualization
  • mediumreadme#3
    Add a comparison section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, perhaps titled 'Why Neuronpedia? / How is this different from X?' or 'Comparison to other tools,' explicitly stating how Neuronpedia differs from general ML visualization tools or other interpretability libraries by focusing on LLM neurons.

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 hijohnnylin/neuronpedia
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
tensorflow/tensorboard
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. tensorflow/tensorboard · recommended 1×
  2. wandb/wandb · recommended 1×
  3. neptune-ai/neptune-client · recommended 1×
  4. pytorch/captum · recommended 1×
  5. shap/shap · recommended 1×
  • CATEGORY QUERY
    What platforms are available for visualizing and interpreting the internal states of AI models?
    you: not recommended
    AI recommended (in order):
    1. TensorBoard (tensorflow/tensorboard)
    2. Weights & Biases (W&B) (wandb/wandb)
    3. Neptune.ai (neptune-ai/neptune-client)
    4. Captum (pytorch/captum)
    5. SHAP (SHapley Additive exPlanations) (shap/shap)
    6. LIME (Local Interpretable Model-agnostic Explanations) (marcotcr/lime)
    7. DeepView.ai

    AI recommended 7 alternatives but never named hijohnnylin/neuronpedia. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I analyze neural network activations and discover circuits within complex AI systems?
    you: not recommended
    AI recommended (in order):
    1. TransformerLens
    2. Captum
    3. Lucid
    4. Neuroscope
    5. Circuits.js
    6. PyTorch
    7. TensorFlow
    8. Interpret-Community

    AI recommended 8 alternatives but never named hijohnnylin/neuronpedia. 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 hijohnnylin/neuronpedia?
    pass
    AI named hijohnnylin/neuronpedia explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of hijohnnylin/neuronpedia. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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hijohnnylin/neuronpedia — 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