RRepoGEO

REPOGEO REPORT · LITE

jennyzzt/dgm

Default branch main · commit a565fd2d · scanned 5/13/2026, 4:18:32 PM

GitHub: 2,041 stars · 414 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 jennyzzt/dgm, 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 specific topics to categorize the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    self-improving-agents, open-ended-evolution, code-evolution, meta-learning, ai-agents, generative-ai, autonomous-systems
  • highreadme#2
    Reposition the README's opening sentence to clarify its category

    Why:

    CURRENT
    Repository for **Darwin Gödel Machine (DGM)**, a novel self-improving system that iteratively modifies its own code (thereby also improving its ability to modify its own codebase) and empirically validates each change using coding benchmarks.
    COPY-PASTE FIX
    The **Darwin Gödel Machine (DGM)** is a novel framework for open-ended evolution of self-improving AI agents, designed to iteratively modify its own code and empirically validate each change using coding benchmarks.
  • mediumhomepage#3
    Add the official project homepage to repository metadata

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://sakana.ai/dgm/

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 jennyzzt/dgm
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
INRIA/spoon
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. INRIA/spoon · recommended 1×
  2. pmd/pmd · recommended 1×
  3. dotnet/roslyn · recommended 1×
  4. Clang LibTooling · recommended 1×
  5. ast module in Python · recommended 1×
  • CATEGORY QUERY
    How can I build a system that automatically refactors and improves its own codebase?
    you: not recommended
    AI recommended (in order):
    1. Spoon (INRIA/spoon)
    2. PMD (pmd/pmd)
    3. Roslyn (.NET Compiler Platform) (dotnet/roslyn)
    4. Clang LibTooling
    5. ast module in Python
    6. go/ast
    7. SonarQube (SonarSource/sonarqube)
    8. OpenRewrite (openrewrite/rewrite)

    AI recommended 8 alternatives but never named jennyzzt/dgm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking frameworks for developing autonomous systems capable of open-ended code evolution and testing.
    you: not recommended
    AI recommended (in order):
    1. OpenAI Gym / Farama Foundation Gymnasium
    2. DeepMind OpenSpiel
    3. Ray RLlib
    4. PyTorch Lightning / TensorFlow Lite
    5. Evotorch
    6. DEAP (Distributed Evolutionary Algorithms in Python)
    7. NEAT-Python (NeuroEvolution of Augmenting Topologies)

    AI recommended 7 alternatives but never named jennyzzt/dgm. 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 jennyzzt/dgm?
    pass
    AI named jennyzzt/dgm explicitly

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

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

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

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jennyzzt/dgm — 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