RRepoGEO

REPOGEO REPORT · LITE

evo-design/evo

Default branch main · commit 6856bba4 · scanned 5/12/2026, 9:27:06 AM

GitHub: 1,508 stars · 178 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
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 evo-design/evo, 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 the Evo 2 mention in the README to clarify Evo 1.x's focus

    Why:

    CURRENT
    # Evo: DNA foundation modeling from molecular to genome scale

**We have developed a new model called Evo 2 that extends the Evo 1 model and its ideas to all domains of life. Please see https://github.com/arcinstitute/evo2 for more details.**

Evo is a biological foundation model capable of long-context modeling and design.
    COPY-PASTE FIX
    # Evo: DNA foundation modeling from molecular to genome scale

This repository contains the Evo 1.x models and code, focusing on long-context DNA sequence analysis and design for prokaryotic genomes.

Evo is a biological foundation model capable of long-context modeling and design.

**We have developed a new model called Evo 2 that extends the Evo 1 model and its ideas to all domains of life. Please see https://github.com/arcinstitute/evo2 for more details.**
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    dna-sequencing, genomic-analysis, biological-foundation-model, language-model, synthetic-biology, machine-learning, deep-learning, bioinformatics, prokaryotic-genomes, long-context-modeling
  • mediumhomepage#3
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    https://www.arcinstitute.org/research/evo

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 evo-design/evo
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
HyenaDNA
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. HyenaDNA · recommended 2×
  2. DNABERT · recommended 2×
  3. Nucleotide Transformer · recommended 1×
  4. Hugging Face Transformers · recommended 1×
  5. Enformer · recommended 1×
  • CATEGORY QUERY
    What tools help with long-context biological sequence modeling for genomic analysis?
    you: not recommended
    AI recommended (in order):
    1. HyenaDNA
    2. DNABERT
    3. Nucleotide Transformer
    4. Hugging Face Transformers
    5. Enformer
    6. Pytorch-Longformer
    7. XGen

    AI recommended 7 alternatives but never named evo-design/evo. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I generate synthetic DNA sequences using a genomic language model?
    you: not recommended
    AI recommended (in order):
    1. Nucleotide Transformer (NT)
    2. GenSLM (Genomic Sequence Language Model)
    3. DNABERT
    4. HyenaDNA
    5. PyTorch
    6. TensorFlow
    7. Hugging Face's `transformers` library
    8. DeepMind's AlphaFold

    AI recommended 8 alternatives but never named evo-design/evo. This is the gap to close.

    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 evo-design/evo?
    pass
    AI named evo-design/evo explicitly

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

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

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

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evo-design/evo — 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