RRepoGEO

REPOGEO REPORT · LITE

TransformerLensOrg/TransformerLens

Default branch main · commit d0e3d8ba · scanned 6/24/2026, 4:16:49 AM

GitHub: 3,592 stars · 613 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
87 /100
Healthy
Category recall
2 / 2
Avg rank #1.0 when recommended
Rule findings
1 pass · 1 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 TransformerLensOrg/TransformerLens, 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 relevant topics to the repository

    Why:

    COPY-PASTE FIX
    mechanistic-interpretability, transformer-models, llm-interpretability, gpt-models, deep-learning-research, pytorch, machine-learning-interpretability
  • mediumreadme#2
    Emphasize granular intervention capabilities in the README's opening

    Why:

    CURRENT
    A Library for Mechanistic Interpretability of Generative Language Models.
    COPY-PASTE FIX
    TransformerLens is a Python library for **mechanistic interpretability** of GPT-style language models, offering **granular access and intervention tools** to reverse-engineer learned algorithms.
  • lowabout#3
    Update the repository description to highlight intervention capabilities

    Why:

    CURRENT
    A library for mechanistic interpretability of GPT-style language models
    COPY-PASTE FIX
    A Python library for **mechanistic interpretability** of GPT-style language models, offering granular access and intervention tools.

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
2 / 2
100% of queries surface TransformerLensOrg/TransformerLens
Avg rank
#1.0
Lower is better. #1 = top recommendation.
Share of voice
15%
Of all named tools, what % are you?
Top rival
Neuroscope
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Neuroscope · recommended 2×
  2. Captum · recommended 2×
  3. CircuitsVis · recommended 1×
  4. EvoJAX · recommended 1×
  5. TensorBoard · recommended 1×
  • CATEGORY QUERY
    Tools for dissecting transformer model behavior and learned algorithms?
    you: #1
    AI recommended (in order):
    1. TransformerLens ← you
    2. Neuroscope
    3. CircuitsVis
    4. Captum
    5. EvoJAX
    6. TensorBoard
    7. PyTorch Debugger
    Show full AI answer
  • CATEGORY QUERY
    Python library to explore and modify activations in pre-trained LLMs?
    you: #1
    AI recommended (in order):
    1. TransformerLens ← you
    2. Hugging Face Transformers
    3. Captum
    4. Neuroscope
    5. PyTorch
    6. TensorFlow / Keras
    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    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 TransformerLensOrg/TransformerLens?
    pass
    AI named TransformerLensOrg/TransformerLens explicitly

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

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

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

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TransformerLensOrg/TransformerLens — 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