RRepoGEO

REPOGEO REPORT · LITE

jennyzzt/dgm

Default branch main · commit a565fd2d · scanned 6/24/2026, 3:18:21 AM

GitHub: 2,130 stars · 429 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
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 clarify project domain

    Why:

    COPY-PASTE FIX
    self-improving-ai, code-generation, evolutionary-algorithms, ai-agents, meta-learning, godel-machine, self-modifying-code
  • highreadme#2
    Reposition README opening to highlight unique self-modification aspect

    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, fully autonomous system for open-ended evolution of self-improving AI agents. Unlike general LLM APIs or agent frameworks, DGM is uniquely designed to iteratively modify its *own source code* (and its ability to do so) and empirically validate each change using coding benchmarks, pushing the frontier of self-modifying intelligence.
  • mediumhomepage#3
    Add the official project homepage URL

    Why:

    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
OpenAI API
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI API · recommended 1×
  2. Anthropic Claude · recommended 1×
  3. Google Gemini · recommended 1×
  4. GitHub Copilot · recommended 1×
  5. huggingface/transformers · recommended 1×
  • CATEGORY QUERY
    How can I build a system that automatically generates and refines its own source code?
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. Anthropic Claude
    3. Google Gemini
    4. GitHub Copilot
    5. Hugging Face Transformers (huggingface/transformers)
    6. DEAP (deap/deap)
    7. GP-learn (trevorstephens/gp-learn)
    8. Microsoft's PROSE (microsoft/prose)
    9. Sketch (snikolov/sketch-frontend)

    AI recommended 9 alternatives but never named jennyzzt/dgm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for tools to evolve AI agents by iteratively modifying their underlying code.
    you: not recommended
    AI recommended (in order):
    1. AutoGPT
    2. GPTEngineer
    3. Smol-Developer
    4. MetaGPT
    5. LangChain
    6. OpenAI's Assistants API
    7. OpenAI's GPT-4
    8. Anthropic's Claude
    9. Google's Gemini

    AI recommended 9 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