RRepoGEO

REPOGEO REPORT · LITE

ehoogeboom/e3_diffusion_for_molecules

Default branch main · commit fce07d70 · scanned 6/15/2026, 5:47:36 PM

GitHub: 566 stars · 140 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 ehoogeboom/e3_diffusion_for_molecules, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    Official code for E(3) Equivariant Diffusion Models (EDM) for generating novel 3D molecular structures, targeting researchers in computational chemistry and drug discovery.
  • highreadme#2
    Clarify the README's opening paragraph to state the problem and audience

    Why:

    CURRENT
    Official code release for the paper Equivariant Diffusion for Molecule Generation in 3D.
    COPY-PASTE FIX
    This repository provides the official code for Equivariant Diffusion Models (EDM), a state-of-the-art method for generating novel and physically consistent 3D molecular structures. It is designed for researchers in machine learning, computational chemistry, and drug discovery seeking advanced tools for molecular design.

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 ehoogeboom/e3_diffusion_for_molecules
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
DiffDock
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. DiffDock · recommended 1×
  2. GeoDiff · recommended 1×
  3. EDM · recommended 1×
  4. Pocket2Mol · recommended 1×
  5. rdkit/rdkit · recommended 1×
  • CATEGORY QUERY
    How to generate novel 3D molecular structures using diffusion models?
    you: not recommended
    AI recommended (in order):
    1. DiffDock
    2. GeoDiff
    3. EDM
    4. Pocket2Mol

    AI recommended 4 alternatives but never named ehoogeboom/e3_diffusion_for_molecules. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What Python libraries exist for 3D molecule generation in drug discovery research?
    you: not recommended
    AI recommended (in order):
    1. RDKit (rdkit/rdkit)
    2. OpenBabel (openbabel/openbabel)
    3. ConfGen
    4. DeepMind's AlphaFold-latest
    5. GraphVAE
    6. MoFlow
    7. PyTorch Geometric (pyg-team/pytorch_geometric)
    8. DeepChem (deepchem/deepchem)
    9. MMFF94
    10. UFF
    11. GAFF

    AI recommended 11 alternatives but never named ehoogeboom/e3_diffusion_for_molecules. 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 ehoogeboom/e3_diffusion_for_molecules?
    pass
    AI named ehoogeboom/e3_diffusion_for_molecules explicitly

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

  • If a team adopts ehoogeboom/e3_diffusion_for_molecules in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ehoogeboom/e3_diffusion_for_molecules 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 ehoogeboom/e3_diffusion_for_molecules solve, and who is the primary audience?
    pass
    AI did not name ehoogeboom/e3_diffusion_for_molecules — 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?

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ehoogeboom/e3_diffusion_for_molecules — 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